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19 Data Analyst Resume Examples - Here's What Works In 2024

The resume is the first step to landing a data analyst role. we interviewed ten hiring managers and recruiters who hire for data analyst roles and found out exactly what they are looking for in 2023. plus, we've compiled six templates you can use when writing your data analyst resume (google docs & pdfs included)..

Data analysts are increasingly becoming one of the most sought after technology roles. Companies are storing terabytes and petabytes of data and need to find ways to effectively use this data to drive business decisions. To do this, they not only need to clean, process and analyze their data, but also need to turn that data into meaningful insights. This is where data analysts come in - i.e. you! In 2023, pretty much every company needs to have a data strategy and, as a result, need to hire data analysts to help with data needs. The first step to getting a data analyst job is a resume. And writing a data analyst resume can be tough if you haven't done it before. In this guide, we've compiled six data analyst resume templates that hiring managers and recruiters have said are among the best data analyst resumes they've seen this year. We've chosen examples of resumes from different stages of the data analyst career path, from entry level to senior level data analysts, so there's a relevant example for you. We've also included links to the PDFs and Google Doc formats, along with specific insight from data-focused recruiters that you can use when writing your own data analyst resume.

Data Analyst Resume Templates

Jump to a template:

• Data Analyst
• Entry Level Data Analyst
• Senior Data Analyst
• Analytics Manager
• Marketing Data Analyst
• Financial Data Analyst
• Experienced Data Analyst
• Junior Data Analyst
• Healthcare Data Analyst
• Business Data Analyst
• Power BI Data Analyst
• Data Analyst Intern

Jump to a resource:

• Keywords for Data Analyst Resumes

Data Analyst Resume Tips

• Action Verbs to Use
• Bullet Points on Data Analyst Resumes
• Frequently Asked Questions
• Related Data & Analytics Resumes

Get advice on each section of your resume:

Template 1 of 19: Data Analyst Resume Example

A data analyst can work in multiple settings by helping companies solve problems through data and statistics. For example, they can work on the marketing team to identify their target audience's shopping habits or trace a disease pattern in a particular area. That’s why they will collect, filter, process, and interpret data. There are many ways to become a data analyst apart from traditional education. You can join an online course, bootcamp, or a certificate program. However, regardless of your educational background, you should emphasize you have advanced training and experience. That’s why it’s a good idea to highlight your data analysis certifications on your resume.

We're just getting the template ready for you, just a second left.

Tips to help you write your Data Analyst resume in 2024

   indicate your knowledge of programming languages..

Depending on your industry and employer, you might get to use a particular programming language to automate data processing. Coding languages like R or Python help data analysts process large sets of data and automate tasks. It is essential to indicate the programming languages you are familiar with on your resume.

   Highlight your data visualization skills.

Even though this is a highly technical occupation, you still need to communicate your results to non-technical stakeholders or team members. That’s why data visualization skills are so important in this role. They help you represent your insights in a more digestible way by using graphics, charts, and even storytelling.

Skills you can include on your Data Analyst resume

Template 2 of 19: data analyst resume example.

This is an effective template you can use if you are applying for all data analyst roles in 2023, and showcases relevant data analyst skill sets in all parts of the resume, including the work experience, skills and projects sections. This resume is ATS-compatible and can be used when applying through online portals. Here's a few more reasons why this data analyst resume template works well:

   Numbers and metrics

Notice how this resume's bullet points makes use of specific numbers while describing accomplishments, e.g. "led to a 25% sales lift". This tells data analyst recruiters that this applicant can make a concrete impact on an organization.

   Good use of space

The two-column in this data analyst resume template prioritizes the work experience sections, while making good use of whitespace. The resume does not look overcrowded and uses reasonable margins.

Template 3 of 19: Entry Level Data Analyst Resume Example

As an entry-level data analyst, you'll be diving into the world of data-driven insights and decision-making. With companies increasingly relying on data for growth and improvement, this role is vital to their success. When crafting your resume, it's essential to demonstrate both your technical skills in data analysis and your understanding of the business context. Keep in mind, employers are looking for candidates with a strong foundation in data manipulation and visualization who can also bring unique insights to the table. In recent years, there's been a shift towards using more advanced tools and programming languages for data analysis, like Python and R. So, ensure your resume highlights your proficiency in these areas, as well as your experience working with databases, data visualization tools, and analytical software. Showcasing your ability to adapt to industry trends will make you stand out among other applicants.

Tips to help you write your Entry Level Data Analyst resume in 2024

   highlight relevant coursework and projects.

As an entry-level candidate, you might not have extensive work experience in data analysis yet. To showcase your skills, focus on relevant coursework, academic projects, or internships that included data analysis tasks. Include specific examples of how you've applied analytical techniques to solve problems or discover insights.

   Demonstrate proficiency in programming languages

Employers often seek data analysts with programming skills in Python, R, or SQL. Make sure to list these languages and any other relevant tools (like Tableau or Power BI) in a "Technical Skills" section of your resume. If possible, include examples of projects that required using these languages to analyze and visualize data effectively.

Skills you can include on your Entry Level Data Analyst resume

Template 4 of 19: entry level data analyst resume example.

If you're a recent graduate or student, use this entry-level data analyst resume template when applying to jobs. It uses extra-curricular and project sections to supplement your work experience.

   University projects

If you are applying for an entry level data analyst job and don't have too much work experience, don't worry! Use data analyst projects like in this resume example to showcase skills like creating predictive models.

   Strong action verbs

Resumes need to use strong action verbs , which immediately tell a recruiter your role in a specific accomplishment. Data analyst resumes should use action verbs that are relevant to data analysis, processing and visualization. Action verbs like "Analyzed", "Assessed" or "Researched" are strong action verbs that effectively showcase data analyst skill sets.

Template 5 of 19: Senior Data Analyst Resume Example

A senior data analyst helps organizations make better business decisions through the use of data and statistical knowledge. They will gather the company’s intelligence and process it to discover actionable insights that help solve a business problem. Hence, senior data analysts will perform data modeling, deep analysis, and forecasting. As a senior data analyst, you might have to supervise less experienced colleagues. Therefore, it is important to mention your ability to monitor team members in your resume. Remember that it’s also important to emphasize your experience in the field.

Tips to help you write your Senior Data Analyst resume in 2024

   demonstrate your impact on previous projects’ success with metrics..

What would you do to showcase your discoveries to your stakeholders? Use metrics and data visualization to represent them. This is the same thing you’ll do with your resume. You should demonstrate your accomplishments with metrics to add tangible value to your resume.

   Indicate your machine learning skills.

Machine learning is an excellent tool that helps you optimize data analytics and data processing. By including this skill in your resume, you are letting your potential employer know that you are up-to-date with the latest industry trends.

Skills you can include on your Senior Data Analyst resume

Template 6 of 19: senior data analyst resume example.

Senior data analyst resumes should have sufficient experience with handling large data sets and experience working cross-functionally. Keep the following in mind too:

   ATS-compatible resume template

Simple templates work well at getting past the automated resume screening stage, also known as the applicant tracking system. Learn how to beat the ATS .

   Strong data analyst skills

Notice how this applicant uses technical data analyst skills in his work experience (e.g. Pentaho Kettle), as well as in a dedicated Technical Skills section at the bottom, where he describes relevant data analyst skills like Python and Excel.

Template 7 of 19: Analytics Manager Resume Example

As an Analytics Manager, you'll be responsible for leading a team of analysts to extract insights from data and drive business decisions. Considering the rapidly evolving nature of this field, it's crucial to stay updated with the latest industry trends and advancements in data analysis tools. When crafting your resume for an Analytics Manager position, emphasize your ability to stay current with industry trends and showcase your strong leadership skills. In your resume, you should highlight your experience in managing analytics projects and delivering actionable insights to stakeholders. It's important to demonstrate your proficiency in a variety of data analysis tools and programming languages, as well as your ability to communicate complex data-driven insights to non-technical team members. Tailor your resume to highlight these key skills and experiences to stand out among other applicants.

Tips to help you write your Analytics Manager resume in 2024

   emphasize data analysis tools and languages.

As an Analytics Manager, you'll need to be proficient in a wide range of data analysis tools and programming languages such as Python, R, SQL, and various data visualization tools. Make sure to highlight your expertise in these areas, including any relevant certifications you may have, to showcase your technical competence.

   Showcase your project management experience

Analytics Managers often lead projects, ensuring their completion on time and within budget. In your resume, describe your experience in orchestrating analytics projects from start to finish, including setting goals, managing resources, and presenting findings to stakeholders. Quantify your achievements when possible to demonstrate the impact of your work.

Skills you can include on your Analytics Manager resume

Template 8 of 19: analytics manager resume example.

Analytics managers are also responsible for managing and monitoring data warehousing. It is the process of collecting data from various sources to discover actionable insights. Some employers might need an analytic manager with warehousing skills. Hence, this is something you might want to mention on your resume. Analytics managers also coordinate data governance, which is the process of maintaining the integrity and security of corporate data. This is another skill you may want to consider including in your resume. Due to the constant data threats, it has become an in-demand skill in the industry.

   Prioritize your technical skills.

Numerous soft skills are essential for an analytics manager's occupation, such as communication, time management, and logical thinking. However, you should prioritize technical competencies, especially in the skills section. This is a highly technical role, so your potential employer might want to know if you are proficient in hard skills like data warehousing, Python, SQL, or data visualization.

   Demonstrate you are up-to-date with the latest industry trends.

Data analytics is a field that requires you to become a lifelong learner, and your potential employer might be looking for that. That’s why you need to demonstrate that you are up-to-date with the latest industry trends. Some of the most recent trends include artificial intelligence and cloud computing.

Template 9 of 19: Analytics Manager Resume Example

Analytics managers are senior-level data analysts that are more focused on managerial responsibilities than on data analyst projects. That said, they need to have a strong understanding of data analysis skill sets, so it's important to include relevant skill sets on your resume.

   Show promotions

For senior data analyst roles, it's important to show recruiters that you have been promoted in the past since this shows leadership. Read this step-by-step guide on how to show a promotion on your resume .

   Relevant experience only

Notice how this analytics manager uses a format on their resume to highlight only impressive accomplishments relevant to the data analyst role they are applying to. Notice how the resume includes a 'Selected Project Experience' which highlights specific analytical projects.

Template 10 of 19: Marketing Data Analyst Resume Example

As a Marketing Data Analyst, you'll be responsible for using data to provide insights and recommendations to marketing teams. This essential role has grown in demand as companies increasingly rely on data-driven decision-making. When writing your resume for this role, it's crucial to showcase your expertise in data analysis, marketing concepts, and communication skills. In today's competitive job market, employers are seeking marketing data analysts who can keep up with the ever-evolving industry trends, such as artificial intelligence, machine learning, and automation. Be sure to highlight your experience and adaptability in these areas on your resume to stand out among other applicants.

Tips to help you write your Marketing Data Analyst resume in 2024

   emphasize marketing and data skills.

When writing your resume, make sure to emphasize your marketing knowledge, such as understanding of customer segmentation, and your data skills, like proficiency in SQL, Python, or R. Demonstrating your ability to combine these skillsets will set you apart as a strong Marketing Data Analyst candidate.

   Showcase relevant projects and results

In the experience section of your resume, highlight relevant projects you've worked on, focusing on the results you've achieved. For example, mention a marketing campaign you've optimized through data analysis, resulting in increased ROI or customer engagement metrics.

Skills you can include on your Marketing Data Analyst resume

Template 11 of 19: marketing data analyst resume example.

Marketing data analysts are essentially data analysts that are focused on marketing and growth initiatives. The skill sets to mention on a marketing data analyst resume are generally exactly the same as other data analyst resumes, but you should also include marketing campaigns or tools in a skills section.

   Target your resume to the job

Resume bullet points describe achievements that are well targeted to the job, such as 'designed campaign strategies'. This is likely aligned to the exact marketing data analyst job description. =

   Good use of action verbs

This data analyst resume uses action verbs like "Identified" and "Spearheaded", which show recruiters that they're a strong data analyst hire.

Template 12 of 19: Financial Data Analyst Resume Example

Financial data analysts are like the fortune tellers of the financial world – they use data to predict future trends and guide business decisions. It's a role that's more complex than ever, especially given the rising influence of big data and AI in the finance sector. When writing your resume, remember that you're not just showing your ability to crunch numbers - you're showcasing your capability to derive meaningful insights from vast amounts of data and convert them into actionable business strategies. The finance industry is evolving fast and companies are relying heavily on data to stay ahead. So, job seekers for this role should reflect that reality in their resumes. This isn't about listing all your past roles and responsibilities; it's about showing how you've used your skills to make a real difference. Companies want analysts who can provide fresh perspectives, help drive efficiencies and enable smart decision-making.

Tips to help you write your Financial Data Analyst resume in 2024

   highlight your quantitative achievements.

Prove your skills with hard data. Instead of simply stating that you're good at data analysis, provide examples where you made a significant impact using your skills. Did your analysis help increase revenue, or reduce costs? Put that in. Quantify your achievements as much as possible.

   Showcase your familiarity with financial systems

You should highlight your experience with financial systems, data platforms, and analytical tools that are widely used in the industry. This might include software like SAS, SQL, Python, or platforms like Oracle, SAP. Mention if you have advanced Excel skills or certification in financial modeling.

Skills you can include on your Financial Data Analyst resume

Template 13 of 19: financial data analyst resume example.

Financial data analysts are just data analysts that are in the financial industry. If you're applying for a data analyst role in 2023, you should include financial data analyst skills like Python and Finance Modeling into your resume.

   Strong resume bullet points

This job seeker uses resume bullet points that are punchy, and most importantly, contain numbers that demonstrate the significance of their accomplishment.

   Leadership and teamwork

This data analyst resume demonstrates good examples of leadership and teamwork with bullet points like 'Managed a cross-functional team'. This tells data analyst recruiters that you have both the hard and soft skills for the job.

Template 14 of 19: Experienced Data Analyst Resume Example

An experienced data analyst collects, stores, and deduces information from large quantities of data. This requires experience with industry-standard data analysis tools, as well as a very analytical and thorough approach to your work. As this position is not an entry-level position, recruiters will be looking to see your previous experience as an analyst as well as an educational history in mathematics, statistics, business, or a similar field. Take a look at this well-structured experienced data analyst resume.

Tips to help you write your Experienced Data Analyst resume in 2024

   include analyst experience outside of data analysis..

There are many transferable skills for analysts in different sectors. So if you have been an analyst outside of data analysis, be sure to include it in your resume. This applicant has included their experience as a financial analyst and business analyst, which are closely related to data analysis.

   Include professional certification and courses in place of a bachelor’s degree.

If you do not have a bachelor’s degree in mathematics, business, statistics, or a similar field, we suggest you pursue professional certification or take online courses. It will indicate to recruiters your level of commitment to your profession and your level of knowledge.

Skills you can include on your Experienced Data Analyst resume

Template 15 of 19: junior data analyst resume example.

A junior data analyst collects and interprets data to help their superiors in their decision-making for the company. As a junior data analyst, you will most likely be working in a team and will be assisting a senior data analyst and/or be answerable to the department head. This position requires collaborative skills as well as strong analytical skills. Recruiters would prefer to see an educational history in mathematics, statistics, or a related field, and a current industry-standard tools list. Take a look at this strong junior data analyst resume.

Tips to help you write your Junior Data Analyst resume in 2024

   show off your collaboration experience..

As a junior data analyst, you will most likely be working as part of a team. So show off any experience where you worked in a team to achieve something impressive. This applicant ‘assisted with developing 7 new mobile apps used by 200k customers’.

   Showcase your tools list.

As a junior data analyst, you will most probably be assigned to do the more grueling data analysis work. Prove to recruiters that you are experienced and capable of doing that by ensuring that your tools list is extensive and current. So if there is a new data analysis tool, ensure you learn how to use it quickly and add it to your tools section.

Skills you can include on your Junior Data Analyst resume

Template 16 of 19: healthcare data analyst resume example.

Healthcare data analysts use data to make beneficial decisions in patient care, medicine, and healthcare center operations. Some of the data you may be looking at includes pharmaceutical data, behavioral data, clinical data, etc. Recruiters will expect you to see a background in the healthcare industry in the experience section of your resume. A bachelor’s degree in a healthcare-related field or a data analysis related field will also be expected. Take a look at this successful resume that shows both.

Tips to help you write your Healthcare Data Analyst resume in 2024

   show your healthcare industry knowledge..

Industry knowledge is particularly important for this position. So be sure to list what sector of healthcare you are particularly knowledgeable about. This applicant has listed health insurance and HIPAA as some of their areas of expertise.

   Include any healthcare industry certification.

Because you will not find a bachelor’s degree called healthcare data analysis, a good way to show that you are particularly knowledgeable and experienced in this particular field/position is to get certification in healthcare data analysis or something very close to that. This applicant has 3 strong related certifications for this position.

Skills you can include on your Healthcare Data Analyst resume

Template 17 of 19: business data analyst resume example.

A business data analyst collates and interrogates data to help with decision-making aimed at optimizing profit and efficiency in a company. This position requires technical skills and also conceptual skills. You will also need to be a good collaborator as you may be working cross-departmentally. A bachelor’s degree in business administration, mathematics, statistics, or a related field would be highly appreciated by recruiters. Extensive experience as an analyst and an up-to-date skills and tools list would also be beneficial.

Tips to help you write your Business Data Analyst resume in 2024

   show your impact on the bottom line..

An easy way to impress recruiters is to quantify your successes. It makes it easier for them to understand your brilliance and helps to set you apart from your competition. This applicant has employed this tactic with much success.

   Highlight your most impressive achievement.

Sometimes your most impressive achievement may get lost amongst your other achievements listed in your ‘work experience’ section. To make sure this doesn’t happen, mention this achievement in the introduction section of your resume. It will be hard for recruiters to miss it.

Skills you can include on your Business Data Analyst resume

Template 18 of 19: power bi data analyst resume example.

As the name suggests, a Power BI data analyst uses Microsoft’s Power BI, to collect and synthesize data to gain information and assist in decision-making in a company. This position requires a Power BI expert, and experience with similar software would be a plus to recruiters as well. As with any other analyst, a recruiter would like to see a bachelor’s degree in mathematics, statistics, or a similar field. But keep in mind that your experience using Power BI is what recruiters will be looking at most. So if you have any Power BI certification, make sure to highlight that.

Tips to help you write your Power BI Data Analyst resume in 2024

   make sure you keep abreast of power bi updates..

Because you are being hired as an expert in Power BI, you need to ensure that you are experienced with the newest version of the software at all times. So make sure you periodically check for updated versions and ensure you mention the newest version of the software in your resume skills section.

   Focus on Power BI keywords/experience only.

Because this is such a specialized position, if you have a wealth of experience in the data analysis field, limit your experience section to Power BI related experience. That is what recruiters will want to concentrate on.

Skills you can include on your Power BI Data Analyst resume

Template 19 of 19: data analyst intern resume example.

A data analyst intern is an entry-level position. You will be working under a superior and will most likely be assigned simple or more mundane tasks as you prove your capabilities. You may not have a lot of experience to list down, so it is important to build out your skills, education, and extra-curricular sections. Take a look at this well-structured resume.

Tips to help you write your Data Analyst Intern resume in 2024

   work on getting certified..

You may not be able to impress recruiters with an extensive work experience section, but where you can impress recruiters and put yourself above your competition is by getting relevant certifications as you prepare to begin your data analyst career. This applicant has 3 impressive certifications.

   Include experience with transferable skills.

You may not have data analysis experience, but you may have other analytical, data-related experience. Even if it is in another field, feel free to include that experience. The skills used are transferable and therefore relevant.

Skills you can include on your Data Analyst Intern resume

As a hiring manager who has recruited data analysts at companies like Google, Amazon, and Microsoft, I've seen countless resumes for this role. The best ones always stand out by showcasing the candidate's technical skills, business acumen, and ability to communicate insights effectively. In this article, we'll cover six essential tips to help you create a compelling data analyst resume that will catch the attention of recruiters and hiring managers.

   Highlight your technical skills and tools

Data analysts use a variety of tools and technologies to collect, process, and analyze data. It's crucial to showcase your proficiency in these areas on your resume. Some key skills to include are:

• Programming languages: Python, R, SQL
• Data visualization tools: Tableau, PowerBI, Google Data Studio
• Statistical analysis software: SAS, SPSS, Stata
• Spreadsheet tools: Microsoft Excel, Google Sheets

When listing these skills, provide specific examples of how you've used them in your previous roles. For instance:

• Used Python and SQL to extract and analyze customer data from a MySQL database, resulting in a 15% increase in customer retention
• Created interactive dashboards using Tableau to visualize sales performance, enabling the sales team to identify top-performing products and regions

   Demonstrate your impact with metrics

Hiring managers want to see the impact you've made in your previous roles. Use metrics to quantify your achievements and show how your work has contributed to business success. Here are some examples:

• Analyzed customer feedback data and identified key drivers of customer satisfaction, leading to a 20% reduction in churn rate
• Developed a predictive model using R to forecast demand for a new product line, resulting in a 25% increase in sales

Avoid using vague or generic statements like:

• Analyzed data to provide insights
• Created reports and dashboards

Instead, be specific about the type of data you analyzed, the insights you uncovered, and the impact your work had on the business.

   Tailor your resume to the job description

Every company has unique data challenges and requirements. To stand out, tailor your resume to the specific job you're applying for. Review the job description carefully and identify the key skills and experiences the employer is looking for. Then, emphasize those skills and experiences in your resume.

For example, if the job description mentions experience with A/B testing, make sure to highlight any relevant projects you've worked on:

• Conducted A/B tests on the company website to optimize user experience, resulting in a 10% increase in conversion rate

Tailoring your resume shows that you've done your research and understand the company's needs. It also helps the hiring manager quickly see how your skills and experiences align with the role.

   Include relevant projects and coursework

If you're a recent graduate or have limited work experience, include relevant projects and coursework on your resume. This can help demonstrate your skills and knowledge to potential employers. For example:

• Capstone project: Analyzed a dataset of 10,000 customer reviews using Python and NLTK to identify sentiment and key themes
• Coursework: Machine Learning (A), Data Structures and Algorithms (A-), Database Systems (B+)

When describing projects, focus on your role, the tools and techniques you used, and the outcomes you achieved. This helps hiring managers understand the depth of your experience and how you can apply it to their organization.

   Showcase your business acumen

Data analysts don't just work with numbers; they also need to understand the business context and communicate insights effectively to stakeholders. Demonstrate your business acumen by highlighting experiences where you've collaborated with cross-functional teams, presented findings to executives, or made data-driven recommendations.

For example:

• Partnered with the marketing team to analyze campaign performance data, identifying opportunities to optimize ad spend and improve ROI by 30%
• Presented quarterly business reviews to senior leadership, communicating key insights and recommendations for strategic decision-making

Showcasing your ability to bridge the gap between data and business strategy will make you a more attractive candidate to potential employers.

   Keep it concise and easy to read

Hiring managers often review dozens of resumes for a single position. To make sure yours stands out, keep it concise and easy to read. Here are some tips:

• Use clear, concise language and avoid jargon or technical terms that may not be familiar to everyone
• Break up long paragraphs into shorter, easier-to-read sections
• Use bullet points to highlight key achievements and skills
• Ensure consistent formatting throughout the document

A well-organized, visually appealing resume will make it easier for hiring managers to quickly identify your qualifications and fit for the role.

Results-oriented data analyst with 5+ years of experience leveraging data to drive business decisions. Proficient in Python, SQL, and Tableau, with a proven track record of collaborating with cross-functional teams to identify opportunities and implement data-driven solutions. Passionate about using data to solve complex problems and deliver meaningful insights.

By following these tips and crafting a compelling resume, you'll be well on your way to landing your next data analyst role.

When writing your data analyst resume, keep in mind the following.

   Structure your bullet points using the Action Verb + Task + Metric framework

Try to always use this framework when writing your bullet points for your data analyst resume. Recruiters are always looking for quantifiable evidence of your impact, and using this framework will ensure you have. Here's what it looks like:

And here's another example:

   Fix your resume's mistakes using Score My Resume

Make sure you upload your resume to Score My Resume to see where you are going wrong and how to improve it.

Writing Your Data Analyst Resume: Section By Section

  header, 1. put your name on its own line.

Your name should be the most prominent part of your header, so it's important to put it on its own line. This will make it easy for hiring managers to quickly identify who you are.

Here's an example of a good name format:

Avoid formatting your name like this:

2. Include your job title

If you're applying for a data analyst position, it's a good idea to include your current or desired job title in your header. This will help hiring managers quickly see that you're a relevant candidate.

Good job title examples:

• Business Intelligence Analyst

Avoid job titles that are too generic or not relevant to data analysis:

• Business Professional

3. Add key contact details

In addition to your name and job title, your header should include your key contact details so hiring managers can easily get in touch with you. At a minimum, include:

• Phone number
• Email address
• LinkedIn profile URL

You can also include your city and state, but there's no need to include your full address. Here's an example of a good contact details format:

[email protected] | 555-123-4567 | linkedin.com/in/johnsmith | Seattle, WA

  Summary

A resume summary, also known as a professional summary or summary statement, is an optional section that goes at the top of your resume, just below your contact information. It provides a brief overview of your professional background, skills, and accomplishments that are most relevant to the job you're applying for.

While a summary is not required, it can be a valuable addition to your resume if you have several years of experience, are changing careers, or want to highlight specific skills or achievements that may not be immediately apparent from your work history. However, if you are a recent graduate or have limited work experience, you may want to skip the summary and focus on other sections of your resume.

It's important to note that you should never use an objective statement instead of a summary. Objective statements are outdated and focus on what you want from an employer, rather than what you can offer them.

To learn how to write an effective resume summary for your Data Analyst resume, or figure out if you need one, please read Data Analyst Resume Summary Examples , or Data Analyst Resume Objective Examples .

1. Tailor your summary to the data analyst role

When writing a summary for a data analyst position, it's crucial to showcase your relevant skills and experience. Hiring managers want to see that you have the technical expertise and analytical mindset needed to succeed in the role.

To do this, highlight your proficiency in key areas such as:

• Data analysis and interpretation
• Statistical modeling and data mining
• Programming languages (e.g., SQL, Python, R)
• Data visualization and reporting
• Problem-solving and critical thinking

For example, instead of a generic summary like this:

Results-driven professional with 5+ years of experience in various industries. Proven track record of success in team environments. Seeking a challenging role that utilizes my skills and experience.

Tailor your summary to the data analyst role:

Data analyst with 5+ years of experience using statistical analysis, data mining, and data visualization to drive business decisions. Proficient in SQL, Python, and Tableau. Proven ability to translate complex data into actionable insights and communicate findings to stakeholders.

2. Quantify your achievements

When possible, use specific numbers and metrics to quantify your accomplishments in your summary. This helps hiring managers understand the impact you've made in your previous roles and how you can contribute to their organization.

For instance, instead of saying:

• Experienced in using data to improve business operations

Quantify your achievement:

• Analyzed customer data to identify opportunities for improvement, resulting in a 15% increase in customer satisfaction scores

Other examples of quantifiable achievements for a data analyst might include:

• Reduced data processing time by 30% by implementing new automation tools
• Developed a predictive model that increased sales by 20%
• Created interactive dashboards that helped executives make data-driven decisions, saving the company $500K annually

By providing concrete examples of your successes, you demonstrate your value and make a stronger case for why you're the best candidate for the job.

  Experience

The work experience section is the most important part of your data analyst resume. It's where you show hiring managers how you've applied your skills to real-world projects and made an impact.

In this section, we'll cover what to include in your work experience section, how to write about your accomplishments, and tips for standing out from other candidates.

1. Focus on relevant data analysis experience

When writing your work experience section, focus on the experience that's most relevant to the data analyst role you're applying for. This could include:

• Analyzing large datasets to identify trends and insights
• Creating data visualizations and dashboards to communicate findings
• Collaborating with cross-functional teams to solve business problems
• Developing and maintaining databases and data pipelines

If you have experience in other areas, like customer service or sales, only include it if you can tie it back to relevant skills for a data analyst, like communication or problem-solving.

2. Highlight your impact with metrics

As a data analyst, metrics are your best friend. Use them in your work experience section to showcase the impact you've had in previous roles. For example:

• Analyzed customer data to identify opportunities for cross-selling, resulting in a 15% increase in revenue
• Created a dashboard to track key performance indicators, reducing time spent on manual reporting by 50%
• Developed a predictive model to forecast inventory demand, reducing stockouts by 20%

Whenever possible, quantify your achievements to give hiring managers a clear picture of your value.

3. Showcase your technical skills

Data analysts use a variety of tools and technologies to collect, analyze, and visualize data. Highlight your technical skills in your work experience section to show hiring managers you have the expertise they're looking for.

For example, instead of just listing 'data analysis' as a skill:

• Conducted data analysis to identify customer trends

Get specific about the tools and techniques you used:

• Analyzed customer data using SQL queries and Python, uncovering insights that led to a 10% increase in customer retention

4. Emphasize your collaboration and communication skills

Data analysts don't work in a vacuum. They often collaborate with cross-functional teams to turn data into actionable insights. Highlight your collaboration and communication skills in your work experience section to show hiring managers you can work effectively with others.

Partnered with the marketing team to analyze campaign data, identifying opportunities to optimize ad spend and increase ROI by 25%

This shows that you can work with other teams to drive business results.

  Education

Your education section is a key part of your data analyst resume. It shows employers that you have the necessary knowledge and training to succeed in the role. Here are some tips to make your education section stand out:

1. Put your education section near the top

If you're a recent graduate or have limited work experience, put your education section near the top of your resume, just below your summary or objective. This will immediately show employers that you have the relevant educational background for a data analyst role.

Here's an example of how to format your education if it's your strongest qualification:

Education Bachelor of Science in Data Science, XYZ University, City, State Graduation: May 2023 GPA: 3.8/4.0 Relevant Coursework: Machine Learning, Data Visualization, Big Data Analytics, Statistical Modeling

2. Include relevant coursework and projects

As a data analyst, you likely took courses and completed projects that are directly relevant to the job. Including these details can make your education section more impactful. List relevant coursework, capstone projects, or your thesis if it shows off data analysis skills.

Here's how you might showcase relevant coursework and projects:

• Relevant Coursework: Data Structures, Algorithms, Database Systems, Data Mining
• Capstone Project: Analyzed customer churn data to identify key factors leading to churn. Built predictive model in Python to forecast churn risk.

3. Add your certifications

Data analysis is a field where certifications carry a lot of weight. If you've earned any relevant certifications, include them in your education section to show your expertise.

Certifications to consider adding:

• Certified Analytics Professional (CAP)
• SAS Certified Advanced Analytics Professional Using SAS 9
• Cloudera Certified Associate (CCA) Data Analyst
• Microsoft Certified: Azure Data Scientist Associate

If you have several certifications, you may want to break them out into their own 'Certifications' section on your resume.

4. Keep it concise if you're experienced

If you're a senior-level data analyst with many years of experience, your education section should be brief. Employers will be more interested in your professional accomplishments. You can simply list your degree, university, and graduation year.

Here's an example of what not to do:

• Master of Science in Applied Mathematics, ABC University, City, State, 2005-2007. Thesis: A Study of Statistical Models for Predicting Housing Prices. Relevant Coursework: Probability Theory, Regression Analysis, Stochastic Processes, Time Series Analysis. GPA: 3.9/4.0

Instead, keep it short and sweet:

M.S. Applied Mathematics, ABC University

Action Verbs For Data Analyst Resumes

Your data analyst resume should contain strong action verbs which effectively describe your accomplishments. Here is a list of action verbs that are popular among strong data analyst resumes. Try not to repeat the same action verb more than twice on your resume. This ensures your accomplishments are unique and stand out.

For a full list of effective resume action verbs, visit Resume Action Verbs .

Action Verbs for Data Analyst Resumes

How to write a data analyst resume.

Here is the process for writing a resume for a Data Analyst role. The steps outlined will guide you to design a resume that shows you have what it takes to clean, process, and analyze business data.

Important information to include in your Data Analyst resume

1.1: include online profiles in your resume header.

Your resume header should include your name, your email address as well as your location. For a specialized role like this, it is advisable to include the job title, Data Analyst, alongside links to your online professional profiles such as GitHub, LinkedIn, and your website.

1.2: List technical Data Analyst skills in the skills section

Adding a skills section will allow you to include keywords that a resume scanner (ATS) is likely to be searching for. Here, you can include relevant hard skills such as 'SQL', 'Python', 'Data Analysis', 'Tableau', and 'Extract, Transform, Load (ETL)'. Organize these skills by proficiency level, and do not list more than 7 items.

Showcase your experience using bullet points

2.1: use strong action verbs and numbers in your bullet points.

Start your bullet points with strong action verbs such as 'Forecasted', 'Analyzed,' and 'Designed'. Action verbs immediately communicate to the recruiter which role you played in a project as a Data Analyst. Your bullet points should always follow the [Action Verb] + [Task] + [Metric] format. Take a look at the following example: Analyzed data from 20000 consumers to develop a multi-tiered pricing model that increased profit margins by 24%. Notice how the bullet point starts with an action verb, 'Analyzed', followed by the task. Also take note of how the bullet point uses a specific number, '24%', to quantify the accomplishment.

2.2: Point out previous promotions to show growth

If applying for a mid or senior Data Analyst role, it is beneficial to demonstrate leadership and managerial skills. You can do this by highlighting promotions that you have received in your past roles. Here are examples of bullet points that demonstrate this: Promoted within one year (a year ahead of schedule) due to strong performance and organizational impact. Promoted to Managing Analyst in 2 years, being the only member in a cohort of 45 Associate Consultants to be fast-tracked

Get past resume scanners (Applicant Tracking Systems)

3.1: use a standard google docs or word template.

Applicant Tracking Systems (ATSs) are automated programs that scan resumes for certain keywords and filter out those that do not meet the role's criteria. To get past the ATS and improve the chances of a Data Analyst recruiter seeing your resume, it is best to make use of Google Docs and Word templates. Be sure to convert your resume to PDF before submitting it.

3.2: Enhance the readability of your resume

Avoid including tables in your resume, as well as the multi-column layout since these can be problematic while parsing by the ATS. Do not submit a scanned copy of your resume as this can make it impossible for the ATS to read.

Finishing touches on your Data Analyst resume

4.1: remove buzzwords and soft skills.

Keywords that describe soft skills such as 'motivated', 'go-getter' and hardworking are best left out of your resume as they serve little purpose. Instead, you should demonstrate these skills through your experience. Below is an example that effectively demonstrates leadership skills without mentioning buzzwords. Deployed the internal tracking system six months ahead of schedule as project manager of an interdepartmental team of 15 people.

4.2: Fix your resume’s mistakes using Score My Resume

It is always a good idea to upload your resume to an online resume checker such as Score My Resume . The free tool will point out areas of your resume that need improvement and catch any errors that you might have missed.

Skills For Data Analyst Resumes

When writing your data analyst resume, you need to make sure you include hard skills in your resume that show recruiters you have the right experience. This not only ensures recruiters put your resume in their 'yes' pile, but this is also ensures your resume will make it past the initial resume screening stage (i.e. the applicant tracking system ). To help you get started, here are keywords and hard skills from data analyst jobs we've analyzed. To find keywords relevant to the job you're applying to, use Targeted Resume . You should always ensure you tailor your resume to the data analyst job posting you apply to. This will maximize your chances getting an interview.

• SAS Programming
• Data Analysis
• Clinical Data Management
• Healthcare Information Technology (HIT)
• Data Visualization
• Electronic Medical Record (EMR)
• Clinical Research
• R (Programming Language)
• Microsoft SQL Server
• U.S. Health Insurance Portability and Accountability Act (HIPAA)
• Data Analytics
• Healthcare Analytics
• Clinical Trials
• Data Management
• Electronic Data Capture (EDC)
• Healthcare Management

How To Write Your Skills Section On a Data Analyst Resumes

You can include the above skills in a dedicated Skills section on your resume, or weave them in your experience. Here's how you might create your dedicated skills section:

Skills Word Cloud For Data Analyst Resumes

This word cloud highlights the important keywords that appear on Data Analyst job descriptions and resumes. The bigger the word, the more frequently it appears on job postings, and the more 'important' it is.

How to use these skills?

Resume bullet points from data analyst resumes.

You should use bullet points to describe your achievements in your Data Analyst resume. Here are sample bullet points to help you get started:

Liaised with marketing to drive email and social media advertising efforts, using predictive modeling and clustering, resulting in a 35% increase in revenue

Built Tableau dashboard to visualize core business KPIs (e.g. Monthly Recurring Revenue), saving 10 hours per week of manual reporting work

Analyzed global opportunities for the company's different membership tiers; designed and introduced a new membership tier which is projected to generate 300k new users in its first year

Created Monte Carlo simulation using Pandas (Python) to generate 30,000 sample portfolios with 8+ constraints

Designed the data pipeline architecture for a new product that quickly scaled from 0 to 100,000 daily active users.

For more sample bullet points and details on how to write effective bullet points, see our articles on resume bullet points , how to quantify your resume and resume accomplishments .

Frequently Asked Questions on Data Analyst Resumes

What should a data analyst put on a resume.

• Header section: Here, include a link to an online profile such as LinkedIn or your portfolio. Your portfolio should showcase your work using visuals, dashboards, and graphs so it can be understood by non-technical hiring managers. It is also a good idea to include your job title—Data Analyst, alongside your name and country/city.

Analyzed data from 20000 consumers to develop a multi-tiered pricing model that increased profit margins by 24%.

• Education: Here, list your qualifications in analytics, statistics, computer science or equivalent areas. Keep this section brief, listing just the certification name, school, and graduation date.
• Skills section.

What skills should you put on a data analyst resume?

How do i improve my data analyst resume, other data & analytics resumes, engineering manager.

Integration Architect

Data Analyst Resume Guide

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• Skills and Keywords to Add
• Sample Bullet Points from Top Resumes
• All Resume Examples
• Data Analyst CV Examples
• Data Analyst Cover Letter
• Data Analyst Interview Guide
• Explore Alternative and Similar Careers

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Experienced Data Analyst CV Example

Cv guidance.

• CV Template
• How to Format
• Personal Statements
• Related CVs

CV Tips for Experienced Data Analysts

• Highlight Your Certifications and Specializations : Mention qualifications like Certified Analytics Professional (CAP) or Certified Data Management Professional (CDMP). Detail specializations such as predictive analytics, data mining, or machine learning early on in your CV.
• Quantify Your Achievements : Use numbers to illustrate your impact, such as "Improved sales forecast accuracy by 20% through predictive modeling" or "Reduced data processing time by 30% by implementing efficient data pipelines".
• Customize Your CV to the Job Description : Align your CV content with the job's requirements, emphasizing relevant experiences like big data handling, data visualization, or statistical modeling, depending on the employer's needs.
• Detail Your Technical Proficiency : List your proficiency in tools like SQL, Python, R, Tableau, or Hadoop. Also, mention your experience with machine learning algorithms, data warehousing, or ETL processes.
• Showcase Your Soft Skills and Leadership : Highlight instances where you've led data projects, collaborated with cross-functional teams, or effectively communicated complex data findings to non-technical stakeholders.

The Smarter, Faster Way to Write Your CV

• Developed and implemented a new data analytics strategy that increased operational efficiency by 30%, leading to significant cost savings and improved business decision-making.
• Led a team of junior data analysts, mentoring them in advanced data analysis techniques and fostering a 20% increase in team productivity.
• Designed a predictive model using machine learning algorithms that accurately forecasted sales trends, contributing to a 15% increase in quarterly revenue.
• Managed the data integrity of over 5TB of business-critical information, implementing data cleaning procedures that reduced errors by 25%.
• Collaborated with cross-functional teams to translate business needs into data analysis projects, resulting in actionable insights that drove a 10% increase in customer retention.
• Introduced advanced data visualization tools, enhancing the understanding of complex data sets and improving the speed of decision-making processes by 35%.
• Conducted comprehensive data analysis that identified key market trends, influencing the company's strategic direction and leading to a 20% increase in market share.
• Automated routine data collection and processing tasks, saving the team an average of 15 hours per week and allowing for more focus on high-level analysis.
• Played a key role in a data migration project, ensuring a smooth transition with zero data loss and minimal downtime.
• Data Analysis
• Data Visualization
• Machine Learning Algorithms
• Data Cleaning
• Team Leadership
• Project Management
• Strategic Planning
• Process Automation
• Data Migration
• Cross-Functional Collaboration

Experienced Data Analyst CV Template

• Partnered with [teams/departments] to analyze [type of data, e.g., customer behavior, sales trends], utilizing [tools/techniques, e.g., SQL, Python, R] to drive [business outcome, e.g., improved marketing strategies, increased sales].
• Managed [data-related task, e.g., data cleaning, data integration], ensuring [quality or standard, e.g., accuracy, consistency] to enhance [operational outcome, e.g., decision-making, reporting efficiency].
• Implemented [system or process improvement, e.g., new data visualization tool, automated data collection], resulting in [quantifiable benefit, e.g., 20% time savings, improved data quality].
• Key contributor to [project or initiative, e.g., predictive modeling, data governance], which led to [measurable impact, e.g., improved forecasting accuracy, enhanced data security].
• Conducted [type of analysis, e.g., statistical analysis, trend analysis], using [analytical tools/methods] to inform [decision-making/action, e.g., business strategies, product development].
• Played a pivotal role in [task or responsibility, e.g., data quality assurance, report generation], ensuring [quality or standard, e.g., data integrity, report accuracy] across all data assets.
• Major: Name of Major
• Minor: Name of Minor

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Data Analyst Resume - Guide & Examples for 2024

Our world is swamped with data.

But we don’t have enough skilled personnel to help us make sense of it all. 

If you want to be a data analyst, then that’s good news for you

Because it’s one of the most in-demand jobs around today.

The World Economic Forum’s 2018 Future of Jobs Report highlighted a growing need for data analysts and predicted these roles – and those of scientists, app and software developers – will experience increasing demand up to 2024.

But what do data analysts do?

• Providing expertise in data storage structures, data mining, and data cleansing
• Translating numbers and facts to inform strategic business decisions
• Analyzing sales figures, market research, logistics, or transport data
• Creating and following processes to keep data confidential
• Coming up with solutions to costly business problems

Knowing what’s likely to pop up in job advertisements for data analysts doesn’t change the fact that writing a resume can be a challenge. And that’s where this guide comes in. 

We’re going to run you through: 

• How to present your contact information
• How to write a strong resume summary
• The 35 must-include skills for data analysts 
• Highlighting your achievements as a data analyst

Let’s look at Lilibeth Andrada’s Novorésumé-created example throughout this guide. 

Data Analyst Resume Sample  

Like the look of this? Create your own modern and professional data analyst resume in minutes with these easy-to-update templates here.

Interested in a different job position? We’ve got more resume examples - just click on one below:

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1. How to Present Your Contact Information

Resumes used to include someone’s full address, but that’s no longer the case. 

It’s fine to include just your city and region instead of your full address.  

Look at what Lilibeth does. 

She gives potential employers her email address and phone number and includes her LinkedIn and GitHub profiles. 

This is a good approach because the LinkedIn profile will allow any non-engineering hiring managers to get a sense of her broader skills and career history, while the GitHub profile will showcase her technical expertise and any past projects or repositories she has worked on.

2. How to Write a Great Data Analyst Resume Summary

Let’s talk about the key content of your resume now. 

And again, let’s use Lilibeth’s resume as we do this. 

Her resume summary is short, positive, and clear. Resume summaries are a key part of your entire resume – because they’re often the first thing hiring managers read.

“Lilibeth’s elevator pitch explains how she is driven, team-oriented and responsible – key character traits in a role where you’ll need to work well with people and ensure that data is gathered and used honestly and accurately.”

Think of your own resume summary as an “elevator pitch” about who you are and what you do. 

Here’s a good and bad example to help you out.

• Thorough and meticulous Data Analyst passionate about helping businesses succeed. Former small business owner and recipient of an MBA. Possessing strong technical skills rooted in substantial training as an engineer.
• I am an enthusiastic Data Analyst with a long history of being interested in math and science. I was the accountant for a friend’s lemonade stand in the third grade. Since then, I’ve gone on to do fundraising for the high school drama club and got an internship at a company owned by my mother’s friend.

3. The 35 Must-include Skills for Data Analysts

Character and past work experience count – but your skills are just as important.  

Since Data Analysis is a highly technical job, be sure to include technical skills , and consider a more general skills section . Do you have any of the skills below? And if you do, which ones are most relevant for the job you’re applying for? 

• Math (statistics and probability)
• Logic and analysis
• Relational databases (MySQL)
• Problem-solving and troubleshooting
• Pattern and trend identification
• Data mining and data QA
• Database design and management
• SharePoint and advanced Microsoft Excel functions
• Tableau and Qlik
• Business intelligence (BI)
• Programming languages
• Risk management
• System administration
• Quantitative methods
• Data warehousing
• Regression analysis
• Data science research methods
• Experimental design & analysis
• Tech support
• Survey creation
• Communication and public speaking
• Clear writing and report writing
• Critical thinking
• Attention to detail
• Risk assessment
• Training and instructing
• Reducing jargon
• Organization
• Teamwork & collaboration
• Project management
• Decision-making
• Time management

4. Highlighting Your Achievements as a Data Analyst

What about your Work Experience? 

Most people list their responsibilities and duties here or even look up old job ads to copy and paste the information. Don’t do that. Instead, flip the work experience section on its head and write about what you’ve achieved – using specific outcomes and results. 

• Completed market analysis, resulting in a 21% increase in sales.
• Used SPSS and MiniTab software to track and analyze data.
• Conducted research using focus groups on 3 different products and increased sales by 11% due to the findings.
• Spearheaded data flow improvement.
• Developed Key Performance Indicators to monitor sales and decreased costs by 17%.

So you should avoid explaining work experience in past roles like this:

• Did market analysis.
• Used computer programs to deal with data.
• Focus groups.

Lilibeth emphasizes her achievements by explaining how her high standards of data adherence at Dell led to her receiving an Employee of the Year award twice in a row. Think of your big contributions in past jobs as an individual contributor or team member.

Are you ready to create your data analyst resume now? 

To prepare for your interview, you can check the following interview questions !

Suggested Reading:

• Resume Formats Guide: How to Pick the Best One
• Best Hobbies & Interests to Put on a Resume
• The Future of Jobs: Fastest Growing Industries [+Infographic]

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14 Data Analyst Resume Examples for Your Dream Job

• Jun 23, 2024
• 1,260 views

Crafting a compelling resume as a data analyst requires showcasing skills and experience succinctly. In this article, we explore 14 effective data analyst resume examples .

The first 5 examples are sorted by the seniority level sharing the best ways of artistically presenting achievements and expertise. The other 9 are tailored to different industries like finance, healthcare, or marketing.

These examples have all that is needed for crafting a masterpiece resume in the dynamic realm of data analysis.

There were 5 exabytes of information created between the dawn of civilization through 2003, but that much information is now created every two days. Eric Schmidt, Executive Chairman at Google

Job overview

A data analyst interprets complex data, extracting insights crucial for business or organizational decisions. They collect, clean, and evaluate data using statistical tools to identify trends and create reports or visualizations.

Collaborating across fields, data analysts provide actionable insights driving strategic decisions and operational improvements.

There is a difference between data scientists and analysts . Data analysts work with the existing information by using the available tools to interpret the statics. Data scientists create these tools as well as the methods that the analysts rely on.

The role of data analysts involves translating data into understandable narratives, necessitating strong analytical skills , and proficiency in programming languages such as Python or R, as well as familiarity with databases and visualization tools like Tableau, Power BI, etc.

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Data analyst resume examples based on job seniority

According to the U.S. Bureau of Labor Statistics , data analysts earn anywhere between $50,440 and $149,640 per year. Naturally, the pay rate depends on the level of expertise as well as the industry.

Below you will find 5 data analyst resume examples for professionals at different stages in their careers . They each follow with an explanation of what is done well in the example and what else can be done to make it even better.

Some of the samples offer fully completed data analyst resume templates , so you can pick the one you like and personalize it based on your level of experience and specific career details.

1. Data analyst intern resume example

If you are a college student looking for an internship to gain real-world application of your knowledge, your resume may look like this:

Areas to improve:

While the summary effectively states goals and aspirations, it's even better to tailor it to the job description . To have a higher chance of being invited for a job interview , the applicant should highlight how their skills and experiences align with the role.

Expanding on the specific tools or methodologies used during the internship will also improve the resume. It will show the application of theoretical knowledge.

Strengths of the example:

• Overall, the resume looks quite strong, especially in terms of how the education section shows relevant coursework . The high GPA indicated academic proficiency and dedication to the career field.
• In addition, the resume highlights hands-on experience gained through an internship. Having tangible projects on GitHub demonstrates initiative and practical application of skills at work.

2. Entry-level data analyst resume example

If you have already graduated from college and looking for your first full-time job , look at the below entry-level data analyst resume sample:

Ryan Garcia Address: 456 Fictitious Ave, Phoenix, AZ Phone: (555) 987-6543 Email: [email protected] LinkedIn: linkedin.com/in/ryangarcia Summary: Result-oriented Data Science graduate with a B.S. in Business Analytics. Proficient in Python, SQL, and data visualization tools. Strong statistical background, adept at deriving actionable insights from complex datasets. Seeking to apply academic knowledge and analytical skills in a data analyst role. Education: BS in Business Analytics, Arizona State University | May 2023 Conducted regression analysis to optimize marketing strategies, resulting in a 25% increase in customer engagement. Led a team project using predictive analytics for inventory management, reducing costs by 15%. Relevant Courses: Data Mining, Business Intelligence, Statistical Analysis. Online Certification in Data Analysis, Stanford University | September 2022 Applied statistical techniques to real-world data sets. Proficient in data manipulation and visualization. Skills: Programming: Python, SQL Data analysis: Pandas, NumPy Data visualization: Tableau, Matplotlib Statistical analysis Machine learning algorithms Work Experience: Data Analyst Intern | Insightful Solutions (Phoenix, AZ) June - November 2023 Analyzed customer behavior patterns, leading to a 10% increase in conversion rates through targeted marketing campaigns. Assisted in building predictive models for sales forecasting, improving accuracy by 20%. Created visually engaging dashboards using Tableau for business stakeholders. Extracurricular Activities: Data Science Club | Treasurer (August 2021 - May 2023) Managed club finances and budget allocation for events and workshops. Organized seminars on emerging trends in data science, fostering collaboration among students.

What can be improved:

Expanding further on the tools, methodologies, or techniques used during the internship will provide more details about the applicant's contributions.

It's also advisable to share how the described skills and knowledge were applied at work or for academic projects.

What's done well:

• Specific achievements with measurable impacts under the education and work experience sections demonstrate practical applications of skills learned in college. Quantifiable accomplishments are strong selling points.
• Involvement in the Data Science Club as a treasurer showcases leadership and organizational skills , which are very valuable in professional settings.

3. Junior data analyst resume example

Areas for improvement:.

While the provided accomplishments are good, it might be better to add more context or specific details to quantify the impact further.

Tailoring the summary section to align more closely with the job description of the role applied will showcase how the skills match the specific requirements of the job.

Strong aspects:

• The work experience section effectively showcases the candidate's responsibilities, accomplishments, and the impact made in their current role . Quantifiable achievements are listed, which is great for showcasing tangible results.
• Participation in conferences and being a speaker at an event is a positive addition, indicating the candidate's involvement and expertise in the field .

4. Mid-level data analyst resume example

Emily Watson 123 Imaginary St., Springfield, IL 62701 | [email protected] | +1 (123) 456-7890 Summary: Detail-oriented data analyst with 4+ years of experience in interpreting and analyzing complex data sets to drive business solutions. Proficient in statistical analysis, data visualization, and SQL. Strong problem-solving skills with a track record of delivering actionable insights. Work experience: Senior Data Analyst | Data Insights Inc. - Springfield, IL (2021-Present) Lead data analysis initiatives, optimizing operational workflows resulting in a 20% increase in efficiency. Develop and implement machine learning algorithms for predictive modeling. Analyze customer behavior patterns to optimize marketing strategies. Data Analyst | Insightful Data Solutions - San Francisco, CA (2017-2019) Built predictive models enhancing inventory management, reducing costs by 15%. Collaborated with cross-functional teams to identify and solve data-related issues. Conducted A/B testing for website optimization, increasing user engagement by 25%. Education: MS in Data Analytics | University of Illinois at Urbana-Champaign (2019-2021) Achieved a 4.0 GPA. Conducted a thesis on predictive analytics in finance. BS in Statistics | University of California, Berkeley (2013-2017) Graduated with honors. Developed predictive models for sales forecasting. Skills: Hard Skills - SQL, Python, Data Visualization, Statistical Analysis, Machine Learning Soft Skills - Problem-solving, Communication, Attention to Detail Certificates: Data Science Specialization, Johns Hopkins University (2020) SQL for Data Science, Udacity (2018)

It might be beneficial to add more details about the tools or methodologies used at work. For example, specifying the software or libraries utilized for data visualization or the machine learning algorithms implemented would be insightful.

Indicating the proficiency level for each skill (e.g., beginner, intermediate, advanced) will provide more clarity to potential employers.

Major strengths of the resume:

• The resume summary effectively outlines the candidate's experience, skills, and achievements, offering a concise overview of their capabilities as a data analyst.
• The candidate showcases progressive experience in the field, detailing achievements with quantifiable results. Each position's responsibilities emphasize the impact made in optimizing processes, implementing models, and improving strategies.

5. Executive level data analyst resume example

Things to make better:.

Including a section on professional development courses completed could further strengthen the resume by showcasing continuous learning and relevant certifications.

Adding specific details or examples of projects handled or tools utilized would provide additional context and depth to the skills listed.

• The work experience section vividly demonstrates progressive responsibilities , showcasing the candidate's impact through quantifiable achievements. The accomplishments are specifically tailored to highlight the strategic implementation of data-driven decisions.
• The abilities mentioned are extensive and cover a broad spectrum of technical, analytical, managerial, and soft skills, showcasing a well-rounded skill set.

Data analyst resume examples based on industry

The top 5 paying industries for data analysts are Computer and Peripheral Equipment Manufacturing; Business Schools and Computer and Management Training; Petroleum and Coal Products Manufacturing; Natural Gas Distribution; and Federal Executive Branch (OEWS Designation).

Below you will find 7 examples of resumes sorted by industry: business, environment, healthcare, etc. Look at these data analyst resume samples to get an idea of how you can improve your self-presentation.

6. Healthcare data analyst resume example

Elena Maxwell Email: [email protected] Phone: (555) 123-4567 LinkedIn: linkedin.com/in/elenamaxwell Summary: Healthcare data analytics professional with expertise in statistical analysis and predictive modeling. Eager to contribute comprehensive knowledge in Python, R, SQL, and healthcare insights to optimize data strategies. Ready to drive meaningful improvements in healthcare analytics within a dynamic organization committed to innovation and excellence. Education: Master of Science in Health Informatics Johns Hopkins University | Baltimore, MD (2018 - 2020) GPA: 3.8/4.0 Thesis: "Utilizing Predictive Analytics in Improving Patient Outcomes in Chronic Disease Management" Bachelor of Science in Statistics University of California | Berkeley, CA (2016 - 2020) GPA: 3.9/4.0 Relevant Coursework: Data Mining, Statistical Modeling, Healthcare Data Management Work Experience: Senior Healthcare Data Analyst at HealthCare Analytics Inc. | Boston, MA (January 2022 - Present) Utilize Python and R to conduct predictive modeling and statistical analysis on patient datasets, employing machine learning algorithms (such as random forests and logistic regression) to forecast patient outcomes. Employ data visualization tools like Tableau and Power BI to create interactive dashboards, enabling stakeholders to grasp complex medical trends easily. Implemented Agile methodologies in data analysis projects, resulting in faster iteration cycles and increased team efficiency. Led the adoption of HIPAA-compliant cloud-based solutions for data storage and processing, ensuring data security while enabling remote access for authorized personnel. Health Data Analyst at Regional Hospital System | New York, NY (June 2020 - December 2021) Conducted comprehensive data analysis using SQL and Excel to identify healthcare utilization patterns and optimize resource allocation. Applied data cleaning techniques and quality improvement methods, utilizing ETL (Extract, Transform, Load) processes to maintain accurate and reliable datasets. Collaborated with IT teams to develop and maintain healthcare databases using SQL Server, ensuring compliance with regulatory requirements. Administered time series analysis and regression models to forecast patient admission rates, aiding in operational planning and resource management. Certificates: Certified Health Data Analyst (CHDA) by the American Health Information Management Association (AHIMA) | 2020 Certified Analytics Professional (CAP) by the Institute for Operations Research and the Management Sciences (INFORMS) | 2020 Skills: Statistical Analysis: Regression Analysis, Hypothesis Testing. Data Visualization: Tableau, Power BI. Programming Languages: SQL, Python. Healthcare Domain Knowledge: Electronic Health Records (EHR), Health Informatics. Predictive Modeling: Machine Learning Algorithms, Time Series Analysis. Publications: Maxwell, E., & Roberts, L. (2023). "Optimizing Healthcare Resource Allocation through Data-Driven Decision-Making" . Healthcare Analytics Review , 8(2), 123-135. Carter, B., Maxwell, E., & Foster, K. (2022). "Predictive Analytics in Chronic Disease Management: A Comprehensive Review" . International Journal of Healthcare Informatics , 15(4), 287-301.

Things to improve:

Adding quantifiable achievements (e.g., percentages, numerical improvements) in the work experience section can further highlight the impact and contributions.

Elaborating further on how the contributions led to specific outcomes would strengthen the impact of the applicant's experience.

What's written well:

• The document begins with a concise and focused resume objective that highlights skills, expertise, and eagerness to contribute to healthcare analytics.
• Each job entry includes specific responsibilities, tools, methodologies used, and achievements, demonstrating practical experience in healthcare data analysis.

7. Business data analyst resume example

Improvement suggestions:.

The skills listed are comprehensive but could benefit from categorization into primary, secondary, or specialized. Additionally, providing context or examples of how these skills were applied in previous roles would be beneficial.

While mentioning certifications and attended conferences is commendable, providing a brief description of these experiences or how they contributed to the candidate's skill set and knowledge could add more value.

Well-done areas:

• The resume opens with a concise and focused career summary. It effectively outlines the candidate's intentions and what they seek in a role as a business data analyst.
• The education section is well-presented, mentioning the relevant coursework and extracurricular activities, and showcases strong academic performance .

8. Market research data analyst resume example

Lucas Bennett [email protected] | +1 (555) 123-4567 | 789 Oak Street, Chicago, IL, 60612 Resume Summary: Data analyst specializing in market research, leveraging statistical insights for strategic business decisions. Proficient in statistical analysis, data mining, and machine learning to optimize market strategies and enhance business performance. Skills: Statistical Analysis . Proficient in conducting regression analysis, hypothesis testing, and advanced statistical modeling using tools like SPSS, SAS, or STATA. Data Mining . Skilled in extracting patterns and trends from large datasets using SQL, Python (pandas, sci-kit-learn), or R (dplyr, tidyr). Data Visualization . Proficient in creating informative dashboards and reports using Tableau, Power BI, and matplotlib or ggplot2 for custom visualizations. Programming . Strong in Python and R for data manipulation, analysis, and modeling, utilizing libraries such as NumPy, SciPy, and pandas in Python and tidyverse in R. Machine Learning . Experienced in applying machine learning algorithms using TensorFlow, sci-kit-learn, or Keras for predictive modeling, classification, and clustering. Work Experience: Market Research Data Analyst at Crimson Insights (Chicago, IL) June 2021 - Present Develop predictive models, improving targeted marketing effectiveness by 15%. Identify new customer segments, expanding the buyer base by 20% through market research. Streamline data collection processes, reducing processing time by 25%. Senior Data Analyst at BlueWave Analytics (New York, NY) October 2019 - May 2021 Analyzed consumer behavior, boosting product satisfaction ratings by 12%. Enhanced reporting efficiency by 30% through data visualization techniques. Implemented automated dashboards for real-time analysis, aiding faster decision-making. Data Analytics Specialist at TechPro Solutions (Seattle, WA) May 2017 - September 2019 Optimized website conversion rates by 18% through A/B testing strategies. Provided key insights for a successful product launch via competitor analysis. Improved predictive analytics for customer preferences by 25% using machine learning. Education: Bachelor of Science in Statistics | University of Wisconsin (Madison, WI) 2013-2017 Relevant Coursework: Advanced Statistical Modeling, Data Analysis Techniques, Time Series Analysis GPA: 3.7/4.0 Corporate Events and Speaking Engagements: Keynote Speaker at the Wisconsin Business Forum 2023 , presenting on "Utilizing Big Data to Drive Market Strategies and Enhance Consumer Engagement". Speaker at the Data Analytics Summit 2022 in Orlando, FL , presenting on "Data-Driven Strategies for Market Growth". Panel Speaker at the Midwest Data Summit 2021 , discussing "Emerging Trends in Predictive Analytics for Market Research".

How to make it better:

The summary is concise but could be more impactful. It might benefit from including more unique selling points or achievements to make it stand out.

While the speaking engagements are impressive, ensuring that they are directly relevant to market research or data analysis could strengthen their impact.

What's presented well:

• The resume is well-organized into clear sections such as Work Experience, Education, Skills, Corporate Events, Speaking Engagements, and Publications, making it easy to navigate.
• The skills section is detailed and comprehensive , highlighting proficiency in various tools, languages, and methodologies essential for a data analyst role in market research.

9. Environment data analyst resume example

Adding any volunteering, research projects , or specific tools/software used in each work experience could further enrich the resume and provide a more comprehensive view of the candidate's capabilities.

Some bullet points could benefit from further quantification or clarification of the impact. For instance, specifying the tools or methodologies used to achieve the improvements mentioned could add depth.

Major strengths:

• The bullet points under each work experience present specific and quantifiable achievements, emphasizing the impact of the candidate's contributions . The inclusion of data-driven results and improvements aids in demonstrating their practical skills in data analysis and environmental research.
• Adding specific courses taken and affiliations with professional organizations indicates ongoing learning, engagement, and networking within the field, showcasing dedication to growth as an environment data analyst.

10. Business intelligence data analyst resume example

Koby Flower 317-471-6587 | [email protected] | 1426 Clay Street Summary: Eager to leverage advanced analytical skills and expertise in data visualization to drive informed business decisions, optimize operational processes, and contribute meaningfully to an innovative team. Work Experience: Business Intelligence Analyst | InsightSphere Dynamics (October 2021 - Present) Phoenix, AZ Develop predictive models that increased sales forecast accuracy by 15%, resulting in a cost-saving of $500,000 annually. Implement Tableau dashboards, improving data visualization and facilitating real-time decision-making processes for senior management. Conduct in-depth market analysis, identifying new customer segments and enabling targeted marketing strategies that boosted ROI by 20%. Data Analyst | Algorithmic Nexus (July 2019 - September 2021) Sacramento, CA Implemented machine learning algorithms that optimized inventory management, resulting in a 25% reduction in excess costs. Conducted A/B testing, driving website optimization strategies that led to a 30% increase in online conversions. Coordinated data-driven initiatives with external partners, fostering strategic collaborations and expanding the client base by 15%. Junior Data Analyst | Algorithmic Nexus (June 2018 - July 2019) Sacramento, CA Automated data cleaning processes, reducing manual workload by 30%, enhancing efficiency, and minimizing errors. Collaborated with cross-functional teams to streamline data collection methodologies, leading to a 25% improvement in data accuracy. Produced comprehensive reports on customer behavior patterns, contributing to a 10% increase in retention rates. Education: Bachelor of Science in Business Analytics | University of California, Berkeley, CA (2014 - 2018) GPA: 3.8 Academic Achievements: Dean’s List for all semesters, recipient of the Excellence in Data Analysis Award for outstanding research in predictive modeling Languages: Fluent in English and Spanish Hobbies: Passionate about photography, organizing community tech workshops, and exploring new hiking trails.

What to do to make it better:

Depending on the specific job requirements or industry standards, it may be beneficial to add a section specifically for technical skills or software proficiencies relevant to the field of data analysis (e.g., Python, R, SQL, etc.).

While the hobbies section is a nice personal touch , showcasing any involvements that might also exhibit relevant skills (e.g., data visualization through photography or teaching others in tech workshops) will strengthen the resume.

Strengths of the resume:

• The career progression is well-documented, showing a transition from a junior role to a more senior position. This progression helps demonstrate increased responsibility, skill development, and leadership potential.
• Each work experience bullet point includes specific, quantifiable accomplishments, such as percentage improvements in sales forecast accuracy, ROI, reduction in costs, etc. These metrics provide concrete evidence of the impact in previous roles .

11. Manufacturing data analyst resume example

The skills section could benefit from better organization. Grouping skills into categories (e.g., analytical skills, software proficiency) would enhance readability and highlight core competencies more effectively.

Providing brief explanations of the significance of a certification could add value and depth to the certifications section. This helps the reader understand the relevance and impact of the credentials earned.

What's good about it:

• The experience section effectively outlines the candidate's roles, responsibilities, and key achievements in previous positions. It quantifies accomplishments, which is beneficial for showcasing tangible contributions .
• Including a section specifically dedicated to professional awards adds value by indicating the candidate's involvement in conferences and recognition within their field. It bolsters their credibility and expertise.

12. Operations data analyst resume example

Paolo Valverde Phone: 916-286-9417 Email: [email protected] Address: 4860 Pearl St Objective: Resourceful and results-oriented data analytics professional. Proficient in leveraging data insights to optimize operational efficiency and drive strategic decision-making. Seeking a challenging role to apply my expertise within an innovative organization. Education: Bachelor of Science in Business Analytics | University of Texas at Austin (2021) GPA: 3.7/4.0 Recipient of the Dean's Merit Scholarship for Academic Excellence Conducted a thesis on "Analyzing Operational Trends in E-commerce" Actively engaged in the Data Analytics Society Work Experience: Operations Data Analyst at NovaLogix (Houston, TX) June 2021 - Present Analyze supply chain data, identifying cost-saving opportunities that led to a 15% reduction in operational expenses within the first year. Develop dynamic Power BI dashboards for real-time inventory monitoring, contributing to a 25% decrease in stockouts. Collaborate cross-functionally to optimize logistics, enhancing on-time delivery performance by 20%. Data Analyst Intern at DataWise Solutions (Dallas, TX) May - August 2020 Contributed to the creation of predictive models, resulting in a 30% increase in inventory accuracy by forecasting customer demand. Conducted root cause analysis, implementing solutions that streamlined processes and reduced operational delays by 18%. Prepared detailed reports and visualizations facilitating strategic decision-making for senior management. Certifications: Supply Chain Analytics Certification - Coursera (Rutgers University) | 2021 Certified Data Analyst Associate - Microsoft | 2020 SQL for Data Science - IBM | 2020 Skills: Data Analysis SQL Statistical Analysis Data Visualization (Power BI, Tableau) Process Optimization Supply Chain Management

If there were any noteworthy projects or skills gained during these certification courses , mentioning them briefly will give more context to the proficiencies obtained.

Ensuring that the skills listed directly align with the job description of the position applied. Tailoring the skills section will emphasize those most relevant to the role.

• The education section is detailed, mentioning GPA, academic achievements, thesis topic, and involvement in relevant extracurricular activities .
• The certifications section is strong and relevant, showcasing a commitment to continuous learning in the field. They add credibility to the candidate's skill set .

13. Social media data analyst resume example

The bullet points in the work experience section vary in length and formatting. Ensuring consistency in bullet point length can improve readability and overall presentation.

While technical skills are important, highlighting soft skills such as collaboration and problem-solving could offer a broader perspective on the candidate's suitability for the role.

Resume's strong aspects:

• The professional summary effectively summarizes the applicant's expertise as a social media data analyst, setting the tone for the rest of the resume.
• The resume mentions specific technologies and tools used in the role, which provides insight into the candidate's technical skills and proficiency in relevant software.

14. Financial data analyst resume example

Eugene T. Fielder [email protected] | 252-599-8535 | Elizabeth City, NC Professional Summary Detail-oriented Financial Data Analyst with a strong background in financial analysis, data modeling, and reporting. Proficient in analyzing complex financial data sets, identifying trends, and providing actionable insights to support strategic decision-making. Skilled in financial forecasting, budgeting, and risk analysis. Education Bachelor of Science in Finance | University of Michigan (Ann Arbor, MI) Graduated: May 2015 Skills Financial Analysis Data Modeling Financial Forecasting Portfolio Management Risk Analysis Financial Reporting Market Research Investment Analysis Advanced Excel Data Visualization Professional Experience Financial Data Analyst | Alpha Investment Partners (Elizabeth City, NC) May 2018 - Present Analyze financial data from various sources, including Bloomberg Terminal, SEC filings, and industry reports, to identify investment opportunities and assess risk profiles. Develop complex financial models and forecasts using Excel and Python, incorporating macroeconomic factors and market trends to support portfolio management decisions. Prepare detailed investment memos and presentations for senior management and clients, outlining investment thesis, valuation analysis, and recommendation rationale. Junior Financial Data Analyst | Unity Trust Bank (Ann Arbor, MI) June 2016 - April 2018 Assisted senior analysts in conducting financial statement analysis and peer benchmarking to evaluate the financial health and performance of corporate clients across diverse industries. Supported cross-functional teams in streamlining data collection processes and enhancing data integrity, resulting in a 20% reduction in data discrepancies and errors. Utilized Tableau to create interactive dashboards and reports, providing actionable insights to investment analysts and senior executives. Certifications Chartered Financial Analyst | CFA Institute (2018) Financial Modeling and Valuation Analyst (FMVA™) | Corporate Finance Institute (2017) Languages Proficient in English and Spanish

Adding specific achievements or quantifiable results to the professional experience section would enhance the impact of the resume.

Depending on the target role or industry, adding sections such as professional affiliations, volunteer experience, hobbies , or relevant projects could further enrich the resume.

Things done well:

• The experience section clearly shows the candidate's responsibilities in previous positions, demonstrating their hands-on experience in financial analysis and data management.
• The inclusion of relevant certifications adds value to the resume and indicates the applicant's commitment to professional development in the field of finance.

Sections to include

Information is the oil of the 21st century, and analytics is the combustion engine. Peter Sondergaard, Global Head of Research at Gartner, Inc.

Creating a strong and effective resume for a data analyst position involves organizing the content into well-defined sections . Below are key components every resume should include.

Contact information

Provide accurate and up-to-date contact details to make it easy for recruiters to reach out to you. Include your full name, phone number, location, email address, and LinkedIn profile (if applicable).

Resume summary or objective

Provide a concise overview of your career goals, skills, and what you bring to the role. A summary is more suitable for experienced professionals, while an objective is often used by entry-level candidates. Focus on how your expertise aligns with the employer's needs.

Create a dedicated section listing your hard and soft skills relevant to data analysis. Include both technical skills (e.g., programming languages, statistical analysis, data visualization tools) and soft skills (e.g., analytical thinking, attention to detail, communication ).

Professional experience

Detail your work history in reverse chronological order, starting with your most recent position. For each role, include your job title, the name of the company, location, and the dates of employment . Provide bullet points outlining your key responsibilities and achievements .

Include information about your educational background, including the degree earned, major, school name, graduation date, and any relevant academic achievements.

Additional sections

Projects Showcase specific data analysis projects you've worked on. For each project: Explain the problem or challenge you addressed. Describe the methods and tools you used. Highlight the outcomes and impact of your analysis on decision-making. Certifications List any relevant certifications in data analysis, machine learning, or related fields. Include the certification name, issuing institution, and the date obtained. Professional memberships Mention memberships in professional organizations, data science communities, or relevant industry groups. This shows your commitment to staying current in the field. Awards Highlight any awards or honors you've received for your work in data analysis. This can add credibility to your achievements. Publications If applicable, include any articles, research papers, or conference presentations related to data analysis. Provide details such as titles, publication dates, and venues. Programming languages If you know any languages relevant to data analysis (e.g., SQL, Python), list them in this section to emphasize your technical proficiency.

Tips and tricks for a good data analyst resume

Remember, your resume is your first impression on potential employers, so make sure it's a clear and compelling snapshot of your skills and experiences as a data analyst.

• Job-Specific Keywords. Identify key phrases from the job description like " data modeling ", " predictive analysis ", or " data visualization ". Integrate these terms naturally into your resume to align with the role.
• Technical Skills Focus. Prioritize technical skills essential for the job. Highlight your expertise in statistical tools (Python, R, etc.), database querying (SQL), data visualization (Tableau, Power BI), and machine learning if relevant.
• Quantifiable Impact. Showcase how your data analysis impacted previous employers. Detail projects where your insights improved efficiency, reduced costs, or increased revenue, using specific metrics.
• Industry Expertise. Emphasize experience relevant to the industry, whether it's healthcare (patient data analysis), finance (risk assessment), e-commerce (customer behavior analysis), or any other sector mentioned in the job description.
• Results-Oriented Approach. Focus on your ability to turn raw data into actionable insights. Emphasize your role in driving decision-making processes and contributing to the company's success.

By tailoring your data analyst resume to emphasize these specific aspects relevant to the job description, you'll increase your chances of standing out as an ideal candidate for the position.

Bonus: Cover letter

Writing an effective cover letter for a data analyst position is crucial for making a strong first impression on potential employers.

Here's how to structure and write a compelling data analyst cover letter:

• Address the cover letter to the hiring manager if possible. If the name is not provided in the job listing, you can use a generic greeting such as "Dear Hiring Manager" or "To Whom It May Concern" .
• Begin with a strong opening that grabs the reader's attention. Mention the specific position you are applying for and briefly express your enthusiasm for the role .
• In the body of the cover letter, elaborate on why you are a strong fit for this position. Focus on key experiences, skills, and achievements relevant to the job. Use specific examples to demonstrate your expertise.
• Align your cover letter with the specific requirements outlined in the job description. Draw connections between your skills and experiences and what the employer is seeking.
• Express genuine enthusiasm for the opportunity to work with the company. Mention specific aspects of the organization, such as its projects, culture, or values, that resonate with you.
• Summarize your interest in the position and reiterate your qualifications. Express your eagerness to discuss how your skills can contribute to the success of the team.
• End the cover letter with a call to action , inviting the employer to contact you for further discussion. Provide your availability for an interview or express your willingness to provide additional information.

Create your professional Cover letter in 10 minutes for FREE

Good example:.

Dear Mr. Bayer,

I am writing to express my interest in the Data Analyst position at DataVortex Analytics, as listed on your company's careers page. With a strong foundation in statistical analysis, data interpretation, and proficiency in various analytical tools, I am confident in my ability to contribute effectively to your team.

In my previous role at Insightful Patterns Ltd., I played a pivotal role in enhancing data-driven decision-making processes. I successfully designed and implemented predictive models that resulted in a 20% improvement in forecasting accuracy, directly contributing to a more streamlined inventory management system.

My proficiency in SQL, Python, and advanced Excel allowed me to extract actionable insights from complex datasets, empowering stakeholders to make informed business decisions.

Your recent project on market segmentation, outlined in the job description, closely aligns with my expertise in segmentation analysis and market profiling. I am eager about the opportunity to apply my skills and contribute to the success of this initiative while advancing the analytical capabilities at DataVortex Analytics.

I am eager to bring my analytical skills to your esteemed organization. With a proven track record of delivering actionable insights and a passion for leveraging data to solve complex problems, I am confident in my ability to make a positive impact on your team.

Thank you for considering my application. I am excited about the prospect of contributing to the success of DataVortex Analytics. I would welcome the opportunity to discuss how my skills align with your needs in more detail.

Laurie Lunsford

Bad example:

Dear Hiring Manager,

I'm writing to apply for the Data Analyst position. I have some knowledge of Excel and data analysis from my college coursework. Though I lack experience, I believe I can learn quickly.

I have a bachelor's degree in a vaguely related field and some exposure to Excel and basic data analysis during my coursework. While I don't have much practical experience in data analysis, I am a fast learner and believe that I can quickly pick up the necessary skills for the job.

I am also proficient in using Microsoft Office, and I am confident in my ability to create basic charts and graphs in Excel. Additionally, I have good attention to detail and can identify patterns in data, which I believe will be beneficial in this role.

I'm available for an interview.

Entry-level cover letter for a data analyst:

In essence, these data analyst resume examples serve as guiding stars in the vast galaxy of job applications. Through strategic alignment of technical skills and industry-specific achievements, crafting a compelling resume becomes an art form.

Ultimately, you can easily represent yourself in the best light by using an online resume builder , which will enable you to stand out in a competitive landscape.

Frequently asked questions

Amanda Baker

Certified Professional Resume Writer

Amanda Baker is a Certified Professional Resume Writer (CPRW) and career coach with over a decade of experience crafting compelling resumes and career marketing tools. As a black resume writer, Amanda brings a distinctive perspective to her work, guided by her commitment to nurturing the next generation of job seekers. Her ultimate goal is to equip young professionals with the skills and knowledge to confidently navigate the competitive job market.

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Entry Level Data Analyst Resume No Experience

Are you a recent graduate or someone looking to transition into a data analyst role but lacking professional experience?

Crafting an entry-level data analyst resume with no experience can be challenging, but it’s not impossible.

In this post, we’ll provide you with a sample resume and a step-by-step guide on how to create a compelling resume that highlights your skills, education, and potential.

Whether you have completed coursework, personal projects, or internships, we’ll help you showcase your abilities and increase your chances of landing that first data analyst position. Let’s dive in!

Sample Resume for Data Analyst With No Experience

Peter Davis (000) 142-7147 [email protected] New York, NY

OBJECTIVE Dedicated and detail-oriented individual with a strong analytical mindset, seeking an entry-level position as a Data Analyst. Bringing a solid foundation in data analysis techniques and tools, including proficiency in SQL and Excel. Eager to apply my skills and contribute to the success of a dynamic team in a data-driven environment.

EDUCATION Bachelor of Business Administration State University, New York, NY – 2023

Data Analysis of Sales Trends Analyzed sales data to identify trends and provide insights for optimizing sales strategies. Utilized Excel to perform data cleaning, aggregation, and visualization.

Customer Segmentation Analysis Conducted segmentation analysis using SQL to categorize customers based on behavior and demographics, providing recommendations for targeted marketing campaigns.

CORE SKILLS

• Data analysis and visualization
• SQL and database management
• Excel and data manipulation
• Statistical analysis

INTERNSHIP EXPERIENCE

Data Analyst Intern ABC Company, New York, NY Dec 2023 – May 2024

• Assisted in analyzing and interpreting data to identify opportunities for process improvement.
• Conducted data cleaning and validation for accurate analysis.
• Created data visualizations to present findings to stakeholders.
• Completed a number of monthly reports.
• Performed study on forecasts, demand, income, capital, and expense.

Volunteer XYZ Company, New York, NY Jun 2023 – Dec 2023

• Prepared income and demand presentations in PowerPoint and Excel.
• Performed marketplace analysis to attain product goals and strategies.
• Lead the planning, recognition, development, and completion of design and changes to keep product metrics reports.

CERTIFICATIONS Introduction to SQL Online Learning Platform, 2023

Data Analysis with Excel Certification ABC Online Course Provider, 2022

ADDITIONAL CAPABILITIES

• Problem-solving and critical thinking
• Strong attention to detail
• Effective communication skills
• Team collaboration

Strong references available

How to Write an Entry-Level Data Analyst Resume with No Experience?

Writing an entry-level data analyst resume without any prior experience can be challenging, but it’s not impossible. Here are a few tips to help you create a compelling resume:

1. Objective or Summary Statement: Begin your resume with a strong objective or summary statement that highlights your skills, education, and enthusiasm for the data analysis field. Even though you may not have professional experience, emphasize your determination to learn and contribute.

2. Education: Showcase your academic background, including your degree, university name, and graduation date. If you achieved any notable academic accomplishments or participated in relevant coursework, be sure to mention them.

3. Coursework and Projects: Highlight any coursework or projects that demonstrate your analytical skills. For example, if you completed projects involving data analysis, statistics, or programming languages such as Python or R, mention them to showcase your practical knowledge.

4. Skills: List the technical and soft skills that are relevant to the data analysis field. Include skills like data manipulation, statistical analysis, data visualization, problem-solving, and critical thinking. Don’t forget to mention any software or tools you are familiar with, such as Excel, SQL, Tableau, or Power BI.

5. Certifications and Online Courses: If you have pursued any certifications or completed online courses related to data analysis, include them in a separate section. This demonstrates your proactive approach to learning and acquiring relevant skills.

6. Internships or Volunteer Work: If you have participated in internships or volunteered in roles that involved data analysis tasks, include them in your experience section. Even if they are not directly related to data analysis, highlight any transferable skills you gained during those experiences.

7. Projects or Personal Works: If you have worked on personal data analysis projects or contributed to open-source projects, showcase them. This highlights your initiative, passion, and ability to apply your skills outside of traditional work settings.

8. Relevant Extracurricular Activities: Mention any relevant extracurricular activities or memberships in data-related clubs or organizations. This demonstrates your active engagement in the field and your commitment to continuous learning.

9. References: If you have any references available, consider including them. These can be professors, mentors, or supervisors who can vouch for your abilities and work ethic.

Keep your resume concise, well-structured, and visually appealing. Tailor it to each specific job application, focusing on the skills and qualifications mentioned in the job description. With a well-crafted resume, you can showcase your potential and increase your chances of landing an entry-level data analyst position.

Recommended:

• Entry Level Data Analyst Cover Letter Sample
• 20 Entry Level Data Analyst Interview Questions and Answers

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• • Developed a predictive model for customer behaviour, increasing marketing campaign effectiveness by 25% through targeted promotions.
• • Led the design and implementation of a custom-built analytics dashboard, resulting in a 40% decrease in report generation time for stakeholders.
• • Managed a cross-functional team in an Agile environment, delivering data-driven strategies that propelled a 15% year-on-year growth in customer retention.
• • Enforced strict data governance policies, ensuring the integrity and security of customer data across multiple cloud platforms, including AWS and Azure.
• • Orchestrated an in-depth analysis of CRM data, unveiling key customer segments and optimising engagement tactics, directly supporting a 20% uplift in loyalty scheme sign-ups.
• • Spearheaded a collaborative project with the Marketing department to refine our customer loyalty program, boosting lifetime value by an average of 30%.
• • Engineered a churn prediction analysis framework, slashing churn rates by 18% through proactive retention initiatives.
• • Automated key reporting processes using Python, reducing time expenditure on routine data tasks by 50%.
• • Devised and implemented an A/B testing framework for email marketing campaigns, enhancing click-through rates by 12%.
• • Cultivated a data-centric culture by leading workshops, improving cross-departmental data literacy and usage efficiency.
• • Facilitated the transition to a Snowflake-based data warehouse, improving analysis scalability and enabling real-time insights.
• • Conducted comprehensive retail data analyses that informed store layout optimisation, lifting sales performance by 10%.
• • Introduced a new reporting suite for analysing marketing performance, enhancing decision-making regarding budget allocation.
• • Collaborated with IT to implement robust data quality checks, ensuring a 99.5% accuracy rate in analytic outputs.
• • Analysed customer segmentation data to support targeted marketing campaigns, resulting in a 15% increase in conversion rates.

Data Analyst CV Examples & Guide for 2024

Your data analyst CV must showcase your proficiency in data manipulation and analysis tools. Highlight your expertise in software such as Excel, R, Python, or specialized tools like Tableau and SQL. It is imperative that you also detail your experience with data modeling, forecasting, and statistical analysis. Demonstrate through concrete examples how your insights have driven decisions or added value to your previous employers or projects.

Resume Guide

CV Format Tips

Summary or Objective?

Experience on Your CV

No Experience?

Top CV Skills

Education & Certifications

Key Takeaways

Navigating through the complexities of data cleansing can often be a perplexing challenge for a data analyst, as it involves sifting through vast amounts of information to correct inaccuracies and inconsistencies. Our guide offers practical strategies and tips to streamline this process, ensuring that you can tackle data cleansing with confidence and efficiency.

• Applying the simplest CV design, so that recruiters can easily understand your expertise, skills, and professional background;
• Ensuring you stand out with your header, summary or objective statement, and a designated skills section;
• Creating your CV experience section - no matter how much expertise you have;
• Using real life professional CV examples to enhance the structure and outline of your profile.

If you still have no muse to write your professional CV, find some more industry-leading examples.

• Lab Technician CV Example
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• Lab Assistant CV Example

How to ensure your profile stands out with your data analyst CV format

• list your experience in the reverse chronological order - starting with your latest roles;
• include a header with your professional contact information and - optionally - your photograph;
• organise vital and relevant CV sections - e.g. your experience, skills, summary/ objective, education - closer to the top;
• use no more than two pages to illustrate your professional expertise;
• format your information using plenty of white space and standard (2.54 cm) margins , with colours to accent key information.

Once you've completed your information, export your data analyst CV in PDF, as this format is more likely to stay intact when read by the Applicant Tracker System or the ATS . A few words of advice about the ATS - or the software used to assess your profile:

• Generic fonts, e.g. Arial and Times New Roman, are ATS-compliant, yet many candidates stick with these safe choices. Ensure your CV stands out by using a more modern, and simple, fonts like Lato, Exo 2, Volkhov;
• All serif and sans-serif fonts are ATS-friendly. Avoid the likes of fancy decorative or script typography, as this may render your information to be illegible;
• Both single- and double-column formatted CVs could be assessed by the ATS ;
• Integrating simple infographics, icons, and charts across your CV won't hurt your chances during the ATS assessment.

Use bold or italics sparingly to draw attention to key points, such as job titles, company names, or significant achievements. Overusing these formatting options can dilute their impact.

The top sections on a data analyst CV

• Technical Skills showcase expertise in data tools.
• Professional Experience details relevant job history.
• Education highlights academic qualifications.
• Data Projects demonstrate real-world application.
• Certifications prove commitment to ongoing learning.

What recruiters value on your CV:

• Detail your proficiency with data analysis software and programming languages such as SQL, Python, R, and any visualisation tools like Tableau or Power BI to showcase your technical skills relevant to the job.
• Emphasise your experience with data modelling and the ability to find trends and patterns, by providing examples of projects where you've effectively analysed datasets to inform decision-making.
• Highlight your understanding of statistical techniques and machine learning methods, if applicable, to demonstrate your ability to perform more advanced data analysis.
• Include any experience with data cleaning and manipulation, stressing your keen attention to detail and the understanding of the importance of data quality in analysis.
• Showcase your ability to communicate results effectively, with examples of reports or dashboards you've created, to illustrate your skills in translating complex data into actionable insights for non-technical stakeholders.

Recommended reads:

• CV Structure: Most Common Formats and Attention-Keeping Sections
• How to Write a CV Heading: Templates, Examples & Guide

Our checklist for the must-have information in your data analyst CV header

Right at the very top of your data analyst CV is where you'd find the header section or the space for your contact details, headline, and professional photo. Wondering how to present your the name of the city you live in and the country abbreviation as your address ;

• Integrate a link to your professional portfolio or LinkedIn profile to further showcase your work;
• Upload your professional photo only if you're applying for jobs outside the UK or US.
• are tailored to the role you're applying for by integrating key job skills and requirements;
• showcase what your unique value is, most often in the form of your most noteworthy accomplishment;
• select your relevant qualifications, skills, or current role to pass the Applicant Tracker System (ATS) assessment.

Examples of good CV headlines for data analyst:

• Data Analyst | SQL Expert | Business Insights | Tableau Certificate | 5+ Years
• Senior Data Analyst | Statistical Modelling | Python | Data Visualisation | MSc Data Science | 10 Years
• Junior Data Analyst | Excel & R | Data Mining Enthusiast | Currently in Advanced Analytics Training
• Lead Data Analyst | Big Data | Risk Management | Certified Analytics Professional | 15+ Years Experience
• Data Analyst III | Forecasting Specialist | Machine Learning | SAS Certified | 7 Years in Retail Analytics
• Data Insights Analyst | Marketing Analytics Focus | A/B Testing Pro | Google Data Analytics Cert | 4 Years

What's the difference between a data analyst CV summary and objective

Why should it matter to you?

• Your data analyst CV summary is a showcasing your career ambitions and your unique value . Use the objective to answer why your potential employers should hire you based on goals and ambitions. The objective is the ideal choice for candidates who happen to have less professional experience, but still meet some of the job requirements.

Before you select which one will be more relevant to your experience, have a look at some industry-leading CV summaries and objectives.

CV summaries for a data analyst job:

• With over 5 years of dedicated experience in data analytics at a leading tech firm, I possess advanced proficiency in SQL, R, and Tableau. My proudest achievement includes developing a predictive model that enhanced business decision-making by 30%.
• Adept in transforming complex data sets into actionable insights, I bring 7 years of experience in financial analysis. Mastering Python and Excel, I have effectively forecasted trends that resulted in a 20% revenue increase for my previous employer.
• Transitioning from a successful 10-year career in marketing, I have developed a strong numerical acuity and a passion for data storytelling. My extensive experience in campaign analysis and customer segmentation will contribute immensely to data-driven strategies.
• Coming from a background in environmental science, I am eager to apply my 6 years of research and statistical analysis skills to the field of data analytics. Acclimatized to manipulating large data sets with SPSS, I am ready to unearth insights that drive sustainable growth.
• As an enthusiastic fresh graduate with a degree in Computer Science and a specialization in Data Science, my objective is to leverage my academic knowledge of Python, SQL, and machine learning to unearth impactful insights and contribute to data-driven strategic development.
• My objective as a career starter is to apply the analytical skills honed during my MSc in Statistics to real-world data challenges. Keen to employ my proficiency in R and statistical analysis to provide innovative solutions and help shape the strategic direction of the company.

Best practices for writing your data analyst CV experience section

If your profile matches the job requirements, the CV experience is the section which recruiters will spend the most time studying . Within your experience bullets, include not merely your career history, but, rather, your skills and outcomes from each individual role. Your best experience section should promote your profile by:

• including specific details and hard numbers as proof of your past success;
• listing your experience in the functional-based or hybrid format (by focusing on the skills), if you happen to have less professional, relevant expertise;
• showcasing your growth by organising your roles, starting with the latest and (hopefully) most senior one;
• staring off each experience bullet with a verb, following up with skills that match the job description , and the outcomes of your responsibility.

Add keywords from the job advert in your experience section, like the professional CV examples:

Best practices for your CV's work experience section

• Delivered insightful reports and visualisations through Power BI and Tableau, boosting business decision-making efficiency by 25%.
• Led a team effort to clean and organise data sets using SQL and Python, resulting in a 30% reduction in data retrieval times.
• Developed and maintained KPI dashboards that provided real-time business intelligence to stakeholders, aiding strategic planning.
• Analysed customer behaviour patterns using statistical techniques, contributing to a 15% increase in targeted marketing campaign success.
• Performed A/B testing on e-commerce website changes, which led to a 20% improvement in conversion rates and customer satisfaction.
• Forecasted sales trends with 95% accuracy by implementing advanced predictive analytics, enabling proactive inventory management.
• Contributed to cost reduction strategies by identifying inefficiencies through data analysis, saving the company over £100,000 annually.
• Implemented a new data governance framework that enhanced data quality and compliance with GDPR regulations.
• Collaborated cross-functionally with engineers and product managers to define metrics and align data analytics with business goals.
• Developed comprehensive predictive models for customer behaviour, increasing marketing campaign effectiveness by 25%.
• Led the analytics for a major product launch, interpreting complex data to inform pricing strategies that maximised profitability.
• Trained and mentored a team of junior analysts, enhancing the department's overall analytical capacity and improving report delivery times by 30%.
• Orchestrated a data consolidation project that reduced data redundancy by 40%, significantly improving data integrity across the organisation.
• Championed the adoption of advanced analytics and BI tools, resulting in a 15% increase in operational efficiency.
• Spearheaded the analysis of sales and inventory data, uncovering insights that led to a 10% reduction in carrying costs.
• Analysed international market trends to advise on potential growth opportunities, which led to a successful expansion into three new markets.
• Performed rigorous A/B testing for website optimisations, enhancing user experience and increasing conversion rates by 5%.
• Created dashboards and reports that enabled key stakeholders to visualise performance metrics and support strategic decision-making.
• Initiated a data governance program that maintained high-quality data standards and facilitated compliance with GDPR regulations.
• Deployed machine learning algorithms to forecast sales trends, which helped to optimise stock levels and resulted in a 20% decrease in overstock.
• Coordinated the migration of data systems to a cloud-based infrastructure, enhancing scalability and reducing system downtime by 60%.
• Performed statistical analysis on large datasets to identify key factors influencing product performance, informating a 10% increase in sales.
• Implemented an automated reporting system that streamlined the generation of monthly financial reports, saving 50 hours of manual work per month.
• Collaborated with cross-functional teams to integrate disparate data sources, enhancing data accessibility and fostering a more data-driven culture.
• Advised on best data practices and strategies for a startup, leading to a robust analytics platform that attracted a second round of venture capital funding.
• Conducted complex data modelling that informed the redesign of a customer loyalty program, increasing repeat customer rates by 18%.
• Delivered actionable insights through regular reporting to executive leaders, which guided decision-making processes and operational improvements.
• Pioneered the use of natural language processing in customer feedback analysis, providing granular insights into customer satisfaction levels.
• Managed a portfolio of analytic projects simultaneously, ensuring timely delivery and accuracy in reporting to stakeholders across the business.
• Designed a real-time analytics platform that tracked web user behaviour, allowing for immediate adjustments to digital marketing campaigns and a 10% increase in ROI within the first quarter.
• Developed a key performance indicator framework for sales data that provided insights into regional performance disparities, guiding targeted sales strategies.
• Automated data extraction and transformation processes, which increased data analysis speed by 40% and supported real-time decision making.
• Collaborated with IT to enhance cybersecurity measures around sensitive data, successfully preventing potential data breaches.

Writing your CV without professional experience for your first job or when switching industries

There comes a day, when applying for a job, you happen to have no relevant experience, whatsoever. Yet, you're keen on putting your name in the hat. What should you do? Candidates who part-time experience , internships, and volunteer work.

• CV Work Experience Section: Organizing, Tailoring, Examples To Use
• CV Job Descriptions: What Are They & How to Use Them

If applicable, briefly mention a situation where things didn’t go as planned and what you learned from it, demonstrating your ability to learn and adapt.

Mix and match hard and soft skills across your data analyst CV

Your skill set play an equally valid role as your experience to your application. That is because recruiters are looking for both:

• hard skills or your aptitude in applying particular technologies
• soft skills or your ability to work in a team using your personal skills , e.g. leadership, time management, etc.

Are you wondering how you should include both hard and soft skills across your data analyst CV? Use the:

• skills section to list between ten and twelve technologies that are part of the job requirement (and that you're capable to use);
• strengths and achievements section to detail how you've used particular hard and soft skills that led to great results for you at work;
• summary or objective to spotlight up to three skills that are crucial for the role and how they've helped you optimise your work processes.

One final note - when writing about the skills you have, make sure to match them exactly as they are written in the job ad. Take this precautionary measure to ensure your CV passes the Applicant Tracker System (ATS) assessment.

Top skills for your data analyst CV:

Data Analysis

Statistical Analysis

Data Modeling

Data Mining

Critical Thinking

Problem-Solving

Attention to Detail

Communication

Time Management

Adaptability

Project Management

Use mini case studies or success stories in your CV to demonstrate how your skills have positively impacted previous roles or projects.

Education and more professional qualifications to include in your data analyst CV

If you want to showcase to recruiters that you're further qualified for the role , ensure you've included your relevant university diplomas. Within your education section :

• Describe your degree with your university name(-s) and start-graduation dates;
• List any awards you've received, if you deem they would be impressive or are relevant to the industry;
• Include your projects and publications, if you need to further showcase how you've used your technical know-how;
• Avoid listing your A-level marks, as your potential employers care to learn more about your university background.

Apart from your higher education, ensure that you've curated your relevant certificates or courses by listing the:

• name of the certificate or course;
• name of the institution within which you received your training;
• the date(-s) when you obtained your accreditation.

In the next section, discover some of the most relevant certificates for your data analyst CV:

• How to Showcase Your Educational Achievements on CV: Examples, Templates, & Guide for 2024
• How to Include CV Coursework on Your CV

Key takeaways

Impressing recruiters with your experience, skill set, and values starts with your professional data analyst CV. Write concisely and always aim to answer job requirements with what you've achieved; furthermore:

• Select a simple design that complements your experience and ensures your profile is presentable;
• Include an opening statement that either spotlights your key achievements (summary) or showcases your career ambitions (objective);
• Curate your experience bullets, so that each one commences with a strong, action verb and is followed up by your skill and accomplishment;
• List your hard and soft skills all across different sections of your CV to ensure your application meets the requirements;
• Dedicate space to your relevant higher education diplomas and your certificates to show recruiters you have the necessary industry background.

Looking to build your own Data Analyst CV?

• CV Examples

Frequently asked questions about Data Analyst CVs:

Q: what qualifications do i need to include on my data analyst cv, q: how should i format my data analyst cv, q: how should i tailor my data analyst cv for different types of job applications.

Best Practises for Emailing Your CV: Tips, Examples & Templates for 2024

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Customer Service Skills on CV: How To Showcase Your Customer Service Experience

The Ultimate Guide to Showcasing Key Skills on Your CV

CV Job Descriptions: What Are They & How to Use Them

How to Showcase In-Demand Leadership Skills Across Your CV

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Data Analyst CV Examples & UK Templates

Data analyst job market and outlook

Important business decisions arising from data analysis may take a while to formulate, but CV-influenced hiring decisions can happen in mere minutes! Keep that in mind when creating an impactful data analyst CV that does justice to your expertise and skills. You only get one chance to make a persuasive first impression, and only a few seconds is how long that chance lasts.

Resume.io offers a wide range of tips and tools to help job seekers turn the heads of hiring managers instantly in their direction.That includes dozens of occupation-specific CV examples and writing guides. In the CV guide you’re reading now, together with the corresponding data analyst CV example, we will look at these topics:

• The role of a data analyst and job market outlook
• How to write your data analyst CV — the correct structure, best format, and some general tips
• Making the most of each CV section: header, summary, employment history, skills, and education
• Layout and design hints for a visually impressive CV document

What does a data analyst do?

Data has become is crucial for organisations in the information age, allowing them to make important decisions that affect their viablity and success on all levels. Data analysts are responsible for taking the data and producing relevant reports that help the business make crucial decisions.

Companies can use data analysts to improve all aspects of their business, from enhancing ad campaigns, and personalising their content to developing better, more popular products.

With a revenue of $524 billion (as of July 2023), Amazon uses big data well. The company stores information for every customer and uses that data for product recommendations, customer experience enhancement, and stronger customer relations.

Businesses seeking to improve their profitability and the effectiveness of advertising and social media, will benefit in countless ways from employing data analysts.

It would be safe to acknowledge that a data analyst career is a secure one. The global big data analytics market size was valued at $271.83 billion in 2022 and is projected to grow from $307.52 billion in 2023 to $745.15 billion by 2030. The demand for data analysts — especially those who are highly skilled and experienced — will continue to grow in the foreseeable future.

How much do data analysts earn?

The average salary for a data analyst working in the UK is £35,000 per annum. Therefore, data analysts are one of the most needed professions globally. However, there are relatively few data analysts whose experience level is high enough to meet the demand. 

How to write a data analyst CV

The standard length of a CV is between one page and should never exceed to pages. Before getting started with writing yours, awareness of the correct structure will keep you on track. With few exceptions, all CVs should include these essential sections:

• Summary (also known as the profile)
• Employment History

In some instances, the last three sections could fall in a different order, usually depending on the degree of professional experience or whether there are educational prerequisites. But for the most part, the sequence of sections follows the outline above, as illustrated by our adaptable data analyst CV example.

No two versions of your data analyst should ever be exactly alike. It’s vitally important to tailor your CV to each job application so it’s 100% relevant. That’s one reason to make sure you carefully scutinise the posted job description and requirements. It’s your best source for customising your resume content and tone accordingly. 

The other reason is to identify keywords and phrases that are obviously important to the employer. These should be used liberally in your CV as a precaution for passing through the automated tracking systems (ATS) that many hiring organisations use to screen online submissions.

Choosing the best CV format for a data analyst

Most job seekers are well-advised to use the reverse chronological format for their CV, which tends to be preferred by employers. Your employment history takes precedence, organised in order from your most recent position back to the earliest.

Some job applicants choose the functional CV format instead, where skills are most prominent, or the hybrid (combination) format. For the majority of data analysts, the reverse chronological CV format is the best choice. 

Located at the top of your CV, the header contains essential contact details that the hiring manager can use to identify you and get in touch with you — ideally for an interview invitation. A distinctive header design can help your CV stand out from all the rest, and make it look more inviting to read.

CV summary example: a quick insight

Every CV should start with an introduction, and this is where your summary comes in. The summary (sometimes called the personal statement or profile ) consists of two or three statements below your CV header that briefly describe your accumulated experience and skills. Done right, it gives hiring managers a good vision of what makes you suitable for the job and where you are in your career.

Your CV summary should hit the high notes of your accomplishments in dynamic, results-oriented action statements. Examples: " successfully initiated a data-led social media program " or " managed the data set for over 1,000 customers to help the business make important product decisions. "

The summary can be tricky to write, and some candidates find it a challenge. We have additional CV samples you can for summary inspiration and ideas, including: 

• computer scientist CV example
• business analyst CV example
• data scientist CV example
• marketing CV example
• project manager CV example
• project manager CV example .

Here is a summary you can modify for your own use from our data analyst CV example.

Experienced and dynamic data analyst with a keen ability for interpreting data and drawing conclusions. Adept in reporting on key metrics and analysing and interpreting trends while providing actionable insights.

Include an achievement

If you want the hiring manager to sit up and take notice from the outset, a significant achievement or two in the CV summary will help. That is, something that ties your abilities with an impressive result, such as: “E ffective market analysis helped attain a 30% sales increase. "

Employment history sample: the first step to success

The next CV section is your employment history, where you will detail your work experience, starting with the most recent and working backwards to the earliest.

Create descriptive bullet points for the most directly relevant duties and achievements in each role, resisting the urge to list everything and dilute the impact.

With no need for the “I” pronoun, start each statement with an action verb such as "analysed," "delivered," "managed," or "supported."  As a data analyst, you are well-equipped to cite tangible outcomes using metrics, which will add weight to your CV. Example: " Contributed to 50% sales boost by conducting effective market analysis ."

Below you’ll find the employment history section from our data analyst CV sample.

Data Analyst, Optimal Radar, Bristol   January 2018 - May 2022 

• Designed and executed data management systems.
• Effectively utilised data sources to understand and troubleshoot performance issues.
• Planned and updated interactive web-based visualisation tools with new data.
• Exercised a logical and methodical approach to problem solving.
• Successfully explained technical aspects of the service to non-technical audiences.
• Collaborated across departments to measure and report performance metrics.
• Conducted statistical analyses, including descriptive statistics and regression modeling.
• Documented data processing and workflows.

Associate Data Analyst, Spectator, Bristol   September 2014 - December 2017 

• Served as a central point of contact to drive business decisions by leveraging deep analytics.
• Provided solid recommendations for new strategies to reduce losses and to retain customers.
• Worked collaboratively with leadership and business partners to identify data for analysis.
• Successfully identified data sources and data attributes that supported business goals.
• Conducted analyses that led to 20 percent increase in product sales.

CV skills example: your key attributes

When compiling your CV list of skills , focus on their value-added impact to the employer. Assess the job specs to understand which skills are most likely to attract the hiring manager's attention.

A data analyst CV should include a balanced blend of hard skills and soft skills . That is, your strengths such as data cleaning, data visualisation, and machine learning should be supported by attributes such as strong attention to detail and problem-solving skills, to name but a few. 

A data analyst will have hard skills, such as data cleaning, data visualisation, and machine learning. They would also need to support these with soft skills, such as strong attention to detail and problem-solving skills – to name but a few.

Use the following skills list from our data analyst CV example for guidance.

• Data Analysis
• Effective Time Management
• Data Clean-ups
• Programming
• Ability to Work in a Team
• Data Authoring
• Leadership Skills
• Customer Service

Data analyst CV education example

College degrees are not always necessary for a data analyst position role, although they can give you an edge over other candidates.

The education section of your data analyst CV should include any postsecondary education qualifications you have, listed in reverse chronological order from highest to lowest level. In that instance, you do not need to mention secondary school graduation. 

Be sure to highlight any on-the-job training or courses you've completed in addition to formal education, showing you are committed to continuous learning and development; this is highly appealing to employers. 

In addition, undertaken courses since you completed higher studies, these will show that you are committed to continuous development; this is highly appealing to employers. 

Check out the data analyst CV education example below.

University of London, Bachelor of Science in Computer Science, London  September 2010 - May 2014 

CV layout and design: success at first glance

Most hiring managers don't have much time to assess job applications in depth. That means it’s vital to make a great visual first impression at first glance

You don't need to overthink the design of your CV,  as long as it’s clean, uncomplicated and easy to read. Recruiters are less interested in creativity than they are in legibility. Your CV must be easy to read and assess quickly and efficiently.

Be aware of fonts

A CV can look messy if it is full of different font types and sizes. Use a consistent font throughout and only change the size for the header or the section headings. Always make sure you use a standard size (10 point or 12 point) throughout to optimise readability.

To get the layout just right, consider using a professionally-designed CV template.

The hassle-free way to get all of the layout layout and design details just right, consider using one of Resume.io's field-tested CV templates with our builder tool.

Key takeaways for a data analyst CV 

• Tailor your CV to suit the specific data analyst job and employer, aimed at your target audience.
• Give the hiring manager insight into what you can achieve as a data analyst by showcasing relevant measurable achievements.
• Use keywords throughout your CV. These can be found on the job specs and will help you bypass the ATS.
• Using an expert-designed CV templates can put you on the road to securing your dream data analyst job as quickly as possible.

Attractive CV templates at your fingertips

Top 17 Data Analyst Resume Objective Examples

Updated July 9, 2023 13 min read

A resume objective for a data analyst position is a concise statement of your professional goals and objectives. It should be tailored to the specific job and serve as an introduction to the rest of your resume. When writing your resume objective, focus on the key skills and experience that make you an ideal candidate for the role. Include keywords from the job description, such as “data analysis”, “data visualization” or “SQL”. You can also mention any certifications or qualifications you have acquired that relate to the role. For example: “Recent graduate with a degree in Computer Science seeking to leverage my knowledge of data analysis, SQL and Tableau to contribute to XYZ Company’s data team.” Make sure your resume objective is clear, concise, and relevant to the position you are applying for.

or download as PDF

Top 17 Data Analyst Resume Objective Samples

• To leverage my data analysis skills and experience to contribute to the growth of a forward-thinking organization.
• To obtain a position as a Data Analyst in which I can utilize my analytical, problem solving and communication skills.
• Seeking an opportunity to utilize my expertise in data analysis and statistical modeling to drive business decisions.
• To secure a position as a Data Analyst where I can use my technical knowledge and experience to provide meaningful insights.
• To join an innovative team that values data-driven decisions and utilizes the latest technologies.
• To apply my knowledge of predictive analytics and machine learning techniques to uncover valuable insights from large datasets.
• To gain employment as a Data Analyst where I can use my strong analytical skills and attention to detail to produce meaningful results.
• Looking for an opportunity to work with a team of professionals utilizing cutting edge technologies in the field of data analysis.
• Seeking an entry-level position as a Data Analyst, utilizing my education in mathematics, statistics, and computer science.
• Aiming for a role as a Data Analyst that will enable me to combine my passion for technology with my ability to analyze complex datasets.
• To acquire a challenging position as Data Analyst where I can apply my knowledge of database management systems and statistical software packages.
• Seeking an opportunity to use my experience in data mining, manipulation, visualization, reporting, forecasting, optimization, and predictive modeling techniques.
• Desire to join an organization that encourages creative problem solving using advanced analytics tools and techniques.
• Looking for an entry-level position as Data Analyst where I can develop new skills while contributing meaningfully towards organizational objectives.
• Searching for an opportunity to apply my strong analytical abilities combined with excellent communication skills in order to solve complex problems related to data analysis.
• Aiming for a role as Data Analyst that allows me the chance to utilize both quantitative methods such as predictive analytics & qualitative approaches such as stakeholder interviews & surveys in order to produce actionable insights from large datasets.
• Aspiring for an opportunity where I can leverage my expertise in SQL & Excel along with advanced analytics tools & techniques like R & Python scripting language in order to generate valuable insights from raw datasets

How to Write a Data Analyst Resume Objective

A data analyst resume objective is a concise statement that outlines the skills and experience you bring to the role and how those strengths can benefit the company. As a data analyst, it’s important to showcase your qualifications in order to get noticed by potential employers. An effective resume objective should be tailored for each job you apply for, highlighting the most relevant skills and experiences that make you an ideal candidate. Here are some tips on how to write an effective data analyst resume objective:

1. Focus on Your Strengths: When writing your data analyst resume objective, focus on your unique talents and capabilities that set you apart from other candidates. Highlight any qualifications or accomplishments that demonstrate your expertise in data analysis, such as certifications or awards.

2. Showcase Your Relevant Experience: If you have previous experience in a similar role, use this opportunity to highlight it in your resume objective. Describe the duties and responsibilities you had in past positions that are applicable to the current job opening.

3. Emphasize Your Value Proposition: Use your resume objective to explain why hiring you would benefit the company. Explain what sets you apart from other applicants and how your skills can help them achieve their goals.

4. Keep It Short & Sweet: Remember that employers often receive hundreds of resumes for a single position so make sure yours stands out by keeping it concise yet impactful. Aim for no more than three sentences when crafting an effective data analyst resume objective; this will help ensure that employers read all of it without getting bored or overwhelmed with too much information.

By following these tips, you can craft an effective data analyst resume objective that will make a great first impression on potential employers and give them insight into why they should hire you over other candidates vying for the same position.

Related : What does a Data Analyst do?

Key Skills to Highlight in Your Data Analyst Resume Objective

In today's data-driven world, the role of a data analyst is becoming increasingly significant and competitive. When crafting your resume objective, it's crucial to highlight specific skills that not only match the job description but also set you apart from other candidates. This section will delve into the key skills you should emphasize in your data analyst resume objective. These skills can range from technical proficiencies, such as knowledge of programming languages and database management, to soft skills like problem-solving abilities and effective communication.

SQL (Structured Query Language) is a critical skill for a Data Analyst as it's the standard language for relational database management systems. Data analysts use SQL to write and execute complex queries for data manipulation and analysis. This skill is crucial in retrieving, manipulating, cleaning, and analyzing large datasets to help businesses make informed decisions. Including SQL in a resume objective shows potential employers that the candidate has the technical ability to handle databases effectively.

Python is a versatile and widely used programming language in the field of data analysis. It is used for collecting, analyzing, interpreting, visualizing, and presenting data. Having Python as a skill demonstrates the ability to perform these tasks effectively. Additionally, Python can be used to automate repetitive tasks and create algorithms for complex data processing, making it a valuable skill for improving efficiency and productivity. This skill also shows that the candidate has a strong technical background and the ability to handle large datasets, which are crucial for a Data Analyst role.

R is a programming language specifically designed for data analysis and visualization. As a Data Analyst, having proficiency in R is crucial as it allows for effective data manipulation, statistical modeling, and report generation. This skill is needed for a resume objective to showcase the ability to handle complex data sets, draw meaningful insights from them, and present these findings in a clear and understandable manner. It also demonstrates a strong technical aptitude which is essential in this role.

Tableau is a powerful data visualization tool used in the Business Intelligence industry. As a Data Analyst, proficiency in Tableau is crucial as it allows for the transformation of raw data into an understandable format. This skill is needed for a resume objective to demonstrate the ability to analyze complex datasets, create visually impactful reports and dashboards, and assist in decision-making processes based on data-driven insights. It shows potential employers that the candidate has the technical skills necessary to handle, interpret and present data effectively.

5. Power BI

Power BI is a crucial skill for a Data Analyst as it is one of the most widely used business intelligence tools that helps in converting raw data into meaningful insights. It aids in creating interactive visualizations, reports and dashboards with self-service business intelligence capabilities. This skill is important to mention in a resume objective because it showcases the candidate's ability to analyze complex data, identify trends and patterns, and provide actionable business insights. It also demonstrates proficiency in using advanced tools for data analysis, which can significantly improve efficiency and accuracy in decision-making processes.

Excel is a crucial skill for a Data Analyst as it is one of the most commonly used tools for data analysis and visualization. It allows analysts to organize, manipulate, and analyze large datasets, create charts and graphs, and conduct statistical analyses. Having Excel skills can help increase efficiency and accuracy in data interpretation. This skill is essential for a resume objective to show potential employers that the candidate has the technical ability to handle data-related tasks effectively.

Hadoop is a crucial skill for a Data Analyst as it is an open-source software framework used for distributed storage and processing of big data sets. Having this skill indicates that the candidate can handle large amounts of data efficiently, perform complex data analysis, and extract valuable insights. This ability is essential in helping businesses make data-driven decisions, improve their strategies, and achieve their objectives. Therefore, mentioning Hadoop in a resume objective can highlight the candidate's proficiency in managing and analyzing big data, making them a strong contender for the role.

A Data Analyst needs the skill of SAS (Statistical Analysis System) because it is a software suite used for advanced analytics, business intelligence, data management, and predictive analytics. It allows the analyst to manage and manipulate existing data to identify trends, patterns, and make forecasts. This skill is crucial for a resume objective as it demonstrates the candidate's ability to handle complex data sets and draw meaningful conclusions that can drive strategic decision-making in a business context.

SPSS (Statistical Package for the Social Sciences) is a software application that is used for statistical analysis. As a Data Analyst, having proficiency in SPSS is crucial as it allows one to manage and organize data effectively, perform complex statistical analyses, and interpret data with accuracy. This skill demonstrates the ability to handle large datasets and draw meaningful insights from them which is a key aspect of a Data Analyst's job role. Therefore, including SPSS as a skill in your resume objective can make you stand out to potential employers as someone who has the technical capability needed for the role.

10. Machine Learning

Machine Learning is a crucial skill for a Data Analyst as it involves the use of statistical techniques to enable systems to improve with experience. A data analyst needs to understand and implement machine learning models to analyze larger sets of data and deliver more accurate results, which in turn can help in making strategic decisions. This skill also showcases the ability to automate complex processes and handle large-scale data operations, which is highly desirable in today's data-driven business environments.

In conclusion, the objective section of your data analyst resume should effectively highlight your key skills. This is an opportunity to showcase your unique abilities and strengths that make you an ideal candidate for the role. The skills outlined should align with the job requirements and demonstrate your ability to add value to the potential employer. Remember, a well-crafted objective can set the tone for the rest of your resume, making it critical to ensure it succinctly captures and presents your most relevant skills.

Related : Data Analyst Skills: Definition and Examples

Common Mistakes When Writing a Data Analyst Resume Objective

A data analyst resume objective is an important section of a data analyst's resume. It is the first thing employers will read, so it needs to make a good impression. Unfortunately, many job seekers make common mistakes when writing their resume objectives that can reduce their chances of getting hired.

The most common mistake is using generic language such as “seeking a challenging position.” This does not tell the employer anything about you or why you would be a good fit for the job. Instead, use specific language to describe your skills and experience that relate to the job requirements. For example, “seeking an opportunity to utilize my expertise in Excel and SQL to create meaningful insights from large datasets."

Another mistake people make is writing too much or too little in their resume objective. You don't want to overwhelm employers with too much information, but you also need to provide enough detail about your qualifications so they understand why you are the right person for the job. Aim for one or two sentences that clearly communicate what makes you stand out from other applicants.

Finally, avoid using cliches such as “hard-working” and “team player” in your data analyst resume objective. These terms are overused and don't give employers any insight into who you are as a professional or what value you can bring to the role. Instead, focus on specific accomplishments that demonstrate your skills and experience related to the position.

By avoiding these common mistakes when writing your data analyst resume objective, you can ensure that your application stands out from the competition and gives employers an accurate picture of who you are as a professional and what unique contributions you can make to their organization.

Related : Data Analyst Resume Examples

A right resume objective for a data analyst should focus on the candidate’s ability to analyze and draw insights from data, while a wrong resume objective would focus on the candidate's desire for a job or salary.

Editorial staff

Brenna Goyette

Brenna is a certified professional resume writer, career expert, and the content manager of the ResumeCat team. She has a background in corporate recruiting and human resources and has been writing resumes for over 10 years. Brenna has experience in recruiting for tech, finance, and marketing roles and has a passion for helping people find their dream jobs. She creates expert resources to help job seekers write the best resumes and cover letters, land the job, and succeed in the workplace.

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162 lies and distortions in a news conference. NPR fact-checks former President Trump

Domenico Montanaro

Former President Donald Trump, the Republican presidential nominee, speaks during a news conference at his Mar-a-Lago estate in Florida on Aug. 8. Joe Raedle/Getty Images hide caption

There were a host of false things that Donald Trump said during his hour-long news conference Thursday that have gotten attention.

A glaring example is his helicopter emergency landing story, which has not stood up to scrutiny .

But there was so much more. A team of NPR reporters and editors reviewed the transcript of his news conference and found at least 162 misstatements, exaggerations and outright lies in 64 minutes. That’s more than two a minute. It’s a stunning number for anyone – and even more problematic for a person running to lead the free world.

Politicians spin. They fib. They misspeak. They make honest mistakes like the rest of us. And, yes, they even sometimes exaggerate their biographies .

The expectation, though, is that they will treat the truth as something important and correct any errors.

But what former President Trump did this past Thursday went well beyond the bounds of what most politicians would do.

Here’s what we found, going chronologically from the beginning of Trump’s remarks to the end:

1. “I think our country right now is in the most dangerous position it’s ever been in from an economic standpoint…” 

The U.S. economy has rebounded from the pandemic downturn more rapidly than most other countries around the world. Growth has slowed in recent months, but gross domestic product still grew at a relatively healthy annual clip of 2.8% in April, May and June – which is faster than the pace in three of the four years when Trump was president. — Scott Horsley, NPR chief economics correspondent

2. “…from a safety standpoint, both gangs on the street…”

We don’t have great, up-to-date data on gang activity in the U.S., but violent crime trends offer a good glimpse into safety in the country. Nationally, violent crime – that includes murder, rape, robbery and aggravated assault – has been trending way down after a surge in 2020, according to the most recent data from the FBI . That data is preliminary and incomplete, covering around three-quarters of the country, but other crime analysts have found similar trends. Crime levels, of course, vary locally : murders are down in Philadelphia, for instance, but up in Charlotte, N.C. — Meg Anderson, NPR National Desk reporter covering criminal justice

3. “...and frankly, gangs outside of our country in the form of other countries that are, frankly, very powerful. They’re very powerful countries.”

The U.S. is not in the “most dangerous position” from a foreign-policy standpoint than ever before. Biden pulled troops out of Afghanistan in his first year in office — though the withdrawal itself was chaotic and a target of much criticism — and since then, U.S. troops have not been actively engaged in a war for the first time in 20 years. The U.S. is supporting Ukraine and Israel, of course, and has troops in Iraq and Syria, but they’re not fighting on any regular basis.

What’s more, however, FBI Director Christopher Wray has said the greatest threat to the country is domestic extremism . And beyond organized groups the very definition of extremism is changing, as fringe ideologies move into the mainstream, and radicalization takes hold amongst parts of the populace. Consider: the Jan. 6 riot at the U.S. Capitol and the assassination attempt on Trump’s life, even with a motive that remains murky at best. Regardless, the call is coming from inside the house, domestic extremism experts warn. Many polls show a sobering degree of support for political violence to drive change. — Andrew Sussman, NPR supervising editor for national security

4-5. “ We have a lot of bad things coming up. You could end up in a Depression of the 1929 variety, which would be a devastating thing, took many years– took many decades to recover from it, and we’re very close to that.”

There is nothing to suggest that a 1930s style Depression is on the horizon for the United States. And the Depression did not take “many decades to recover from.” It ended during World War Two , in 1941. — Scott Horsley

6. “And we’re very close to a world war. In my opinion, we’re very close to a world war.”

No serious person thinks that the U.S., Russia and China are about to start a world war. Right now, Russia appears to be having a hard time defending Russia, given Ukraine’s recent incursions. While there are concerns about things like the potential for regional conflagrations in the Middle East, only Trump is talking about world war. — Andrew Sussman

7. “ Kamala's record is horrible. She's a radical left person at a level that nobody's seen.” 

It’s debatable how liberal Harris is. Some in California didn’t like her record on criminal justice and thought she was not progressive enough. She’s clearly liked by progressives and her voting scores as a senator are on the liberal end of the spectrum, but is she “radical left” and “at a level that nobody’s seen”? There are plenty of people alive and in history who would be considered far more liberal and more radical.

8. “She picked a radical left man.”

Few, if any, reasonable people would say Walz is a “radical left man.” He had a progressive record as governor with a Democratic legislature, but the things passed are hardly radical – free school lunch, protecting abortion rights, legalizing marijuana, restricting access to certain types of guns. All of these things have majority support from voters. What’s more, that “progressive” record ignores Walz’s first term as governor when he worked with Republicans because Democrats didn’t control the legislature. And it ignores Walz’s time as a congressman when he was considered a more moderate member given that he was from a district that had been previously held by a Republican.

9. “He's going for things that nobody's ever even heard of. Heavy into the transgender world.” 

Last year, Walz championed and signed a bill that prevented state courts of officials from complying with child-removal requests, extraditions, arrests or subpoenas related to gender-affirming health care that a person receives or provides in Minnesota. “Heavy into the transgender world” is vague and misleading.

10. “He doesn't want to have borders. He doesn't want to have walls.”

Walz has never called for having no borders. He has voiced opposition to a wall because he doesn't think it will stop illegal immigration. He told Anderson Cooper on CNN , for example, that a wall "is not how you stop" illegal immigration He called for more border-control agents, electronics and more legal ways to immigrate.

11. “He doesn't want to have any form of safety for our country.”

Trump himself praised Walz’s handling of the aftermath of the George Floyd murder at the hands of a police officer. And it’s certainly hyperbole to say he “doesn’t want any form of safety for our country.” Walz served in the U.S. National Guard for 24 years, so clearly, he’s interested in the country having national security. And domestically, he’s never been a “defund the police” advocate. Walz opposed a ballot measure that would have gotten rid of minimum police staffing levels, for example. That angered advocates. He signed police reforms into law , but that does not prove wanting no safety.

12. “He doesn't mind people coming in from prisons.”

Walz has not said he wants people coming in from prisons. Trump is trying to tie his claim that other countries are sending prisoners to the United States to Democrats’ immigration policies.

13. “And neither does she, I guess. Because she's not, she couldn't care less.”

Harris has said a lot to the contrary of not caring about the levels of migrants coming across the border, let alone people coming in from prisons. In fact, when in Guatemala, she said her message for people thinking of immigrating to the United States was: " Do not come. Do not come ."

14. “She's the border czar. By the way, she was the border czar, 100%. And all of a sudden, for the last few weeks, she's not the border czar anymore, like nobody ever said it.”

Harris was never appointed “border czar.” That’s a phrase that was used incorrectly by some media outlets. Biden tasked Harris with leading the “ diplomatic effort ” with leaders in Central American countries, where many migrants are coming from.

Biden said he wants Harris “to lead our efforts with Mexico and the Northern Triangle and the countries that help — are going to need help in stemming the movement of so many folks, stemming the migration to our southern border.” He added that Harris “agreed to lead our diplomatic effort and work with those nations to accept — the returnees, and enhance migration enforcement at their borders — at their borders.”

Harris herself that day spoke of “the need to address root causes for the migration that we’ve been seeing.”

15. “We have a very, very sick country right now. You saw the other day with the stock market crashing. That was just the beginning. That was just the beginning.”

The stock market did not “crash.” The stock market fell sharply at the end of last week as investors fretted about a softening job market. This was amplified on Monday when Japan’s stock market tumbled 12%, sparking a selloff around the world. Stocks in Japan and elsewhere have since regained much of this ground, however. The Dow Jones Industrial Average jumped 683 points on the day of Trump’s news conference. — Scott Horsley

16. “Fortunately, we've had some very good polls over the last fairly short period of time.”

Most good polls have shown Harris gaining not just nationally, but also in the swing states, though these same polls show a very close race.

17. “Rasmussen came out today. We're substantially leading.” 

Trump is not substantially leading, and Rasmussen is viewed as one of the least credible pollsters in the country.

18. “And others came out today that we're leading, and in some cases, substantially, I guess, MSNBC came out, or CNBC came out also, with a poll that was, you know, has us leading.” 

Polls have not shown substantial leads. CNBC had Trump leading by 2, unchanged from his 2-point lead in July.

19. “And leading fairly big in swing states. In some polls, I'm leading very big in swing states… .”

Again, polls in swing states have shown a tightened race.

20. “But as a border czar, she's been the worst border czar in history, in the world history.”

Vice President Harris was never asked to lead immigration policy. That’s the job of Homeland Security Secretary Alejandro Mayorkas. Again, the term “border czar” was used inaccurately by some media outlets, and it’s a term conservatives have been using to attack her, in part, because she has only visited the Southern U.S. border a few times since 2021. But in reality, Harris was tapped by President Biden to address the root causes of migration . Her approach has focused on deterrence. She’s told migrants to not come to the U.S., and she has been able to secure more than $5 billion in commitments from private companies to help boost the economy in Central American countries. — Sergio Martínez-Beltrán, NPR immigration correspondent based in Texas 

21. “I think the number is 20 million, but whether it's 15 or 20, it's numbers that nobody's ever heard before. 20 million people came over the border in the last– during the Biden-Harris administration. Twenty-million people. And it could be very much higher than that. Nobody really knows what the number is.”

It’s unclear where Trump is getting this number from. According to U.S. Customs and Border Protection , since 2021 agents have had more than 7.3 million encounters nationwide with migrants trying to cross into the country illegally. Under Biden, unlawful crossings hit an all-time high last year, but that number has decreased significantly, in part, due to Biden’s asylum restrictions at the Southern U.S. border. An April report from the Office of Homeland Security Statistics found there’s nearly 11 million unauthorized migrants in the country. — Sergio Martínez-Beltrán

22. “Just like far more people were killed in the Ukraine-Russia war than you have reported.”

Neither Russia nor Ukraine is revealing its own casualty figures, so there are only very broad estimates. — Andrew Sussman 

23. “A lot of great things would have happened, but now you have millions and millions of dead people. And you have people dying financially, because they can't buy bacon; they can't buy food; they can't buy groceries; they can't do anything. And they're living horribly in our country right now.”

Grocery prices actually jumped sharply during Trump’s last year in office, as pandemic lockdowns disrupted the food supply chain and Americans were suddenly forced to eat more of their meals at home. Grocery inflation in June 2020 hit 5.6%. This was masked, however, by a plunge in other prices, as the global economy fell into pandemic recession.

As the economy rebounded, prices did, too. Inflation began to rise in 2021, and spiked in 2022 after Russia’s invasion of Ukraine sent food and energy prices soaring. Inflation has since moderated, falling from a peak of 9.1% in June 2022 to 3% in June 2024 . (July’s inflation figures will be released next week.) Grocery prices have largely leveled off in the last year, although they remain higher than they were before the pandemic – a potent reminder of the rising cost of living.

Economists have warned that Trump’s proposed import tariffs and immigration restrictions could result in higher inflation in the years to come. Researchers from the Peterson Institute for International Economics estimate the tariffs alone would cost the typical family about $1,700 a year . — Scott Horsley

24. “We've agreed with NBC, fairly full agreement, subject to them, on Sept. 10th.”

This is ABC, not NBC.

25. “She can't do an interview. She's barely competent and she can't do an interview.” 

Harris hasn’t done interviews since getting into the campaign, but she has done them in the past, so saying “she can’t do” one or that she is “barely competent” are just insults. Trump tends to revert to questioning the intelligence of Black women who challenge him. In fact, Trump did it nine times in this news conference, saying either Harris is not that “smart” (five times) "incompetent” (three times) or “barely competent,” as he did here.

26-27. “Why is it that millions of people were allowed to come into our country from prisons, from jails, from mental institutions, insane asylums, even insane asylums, that's a– it's a mental institution on steroids. That's what it is.”

Immigration experts have said they have not been able to find any evidence of this. Adam Isacson, director for defense oversight at the Washington Office on Latin America, told FactCheck.org : “It’s hard to prove a negative — nobody’s writing a report saying, ‘Ecuador is not opening its mental institutions’ — but what I can say is that I work full-time on migration, am on many coalition mailing lists, correspond constantly with partners in the region, and scan 300+ RSS feeds and Twitter lists of press outlets and activists region wide, and I have not seen a single report indicating that this is happening. … As far as I can tell, it’s a total fabrication.”

Notably, a version of this did happen in 1980 during the Mariel boatlift from Cuba . The Washington Post noted three years later: “Back in 1980, it seemed to be a humanitarian and patriotic gesture to accept provisionally, without papers or visas, all those fleeing from the port of Mariel. More than 125,000 came. Most were true refugees, many had families here, and the great majority has settled into American communities without mishap. But the Cuban dictator played a cruel joke. He opened his jails and mental hospitals and put their inmates on the boats too.”

Without a question, some migrants who have come into the U.S. have committed crimes, but the data show the vast majority do not. According to Northwestern University , immigrants are less likely to commit a crime than U.S.-born people and certainly at no higher rates that the population writ large. (Trump goes on to repeat this claim minutes later in the news conference as well, so it is included in our count here.)

28. “We have a president that's the worst president in the history of our country.”

Trump may have this opinion, but he says it as if it’s fact, and a 2022 survey of historians ranked Biden in the top half of presidents. Trump, on the other hand, was No. 43. The two below Trump were James Buchanan, who did little to stop the impending U.S. Civil War, and the impeached and nearly convicted Andrew Johnson.

29. “We have a vice president who is the least admired, least respected, and the worst vice president in the history of our country.” 

A recent rating of vice presidents did not show this. Harris was in the bottom half of vice presidents, but Spiro Agnew, Dan Quayle, Henry A. Wallace and were toward the bottom of the list.

30. “The most unpopular vice president.”

This might have been true about a year ago or so, but not anymore. An NBC poll then showed Harris had the lowest favorability rating of any modern VP they’d tested. But her numbers have turned around. The NPR poll had Harris with a 46%/48% favorable to unfavorable rating, which was higher than Trump’s and his running mate, JD Vance, who is among the least popular running mates in recent history .

31. “Don't forget, she was the first one defeated. As I remember it, because I watched it very closely, but she was the first one.”

Harris was not “defeated,” because she dropped out of the Democratic presidential race before Iowa. But even if one considers her dropping out on Dec. 3, 2019, a defeat, she was not the first of the Democratic candidates in that primary campaign to do so. At least 10 others dropped out sooner .

32-34. “And I'm no Biden fan, but I'll tell you what, from a constitutional standpoint, from any standpoint you're looking at, they took the presidency away. … And they took it away.” 

There’s nothing in the U.S. Constitution about picking presidential candidates. This is a party process, and everything has been done within party rules. And, again, the presidency wasn’t taken away: Biden is still president.

35. “They said they're going to use the 25th Amendment.”

This was never floated as a possibility to get Biden to withdraw from the race. Biden’s Cabinet members are all people he appointed and who are loyal to him. In addition, the 25th Amendment outlines a procedure for removing a sitting president from office, not from running for a second term.

36-39. "They're going to hit you hard. ‘Either we can do it the nice way. I heard, I know exactly, because I know a lot of people on the other side, believe it or not. And, they said, ‘We'll do it the nice way, or we'll do it the hard way.’ And he said, ‘All right.”

This was not said; he did not hear; no Democrats in the know are talking to Trump; and this dialogue is made up.

40. “We're leading, we're leading.”

The race is statistically tied in national polls and in the states. In some national polls, Harris leads. In some, Trump does.

41-42. “I'm saying it's a–, for a country with a Constitution that we cherish, we cherish this Constitution to have done it this way is pretty severe, pretty horrible. … But to just take it away from him, like he was a child.”

Again, this is Trump talking about how Biden stepped aside, and there’s nothing in the Constitution about how the political parties should pick candidates. And nothing was taken away.

43-46. “And he's a very angry man right now, I can tell you that. He's not happy with Obama, and he's not happy with Nancy Pelosi. Crazy Nancy, she is crazy, too. She's not happy with any of the people that told him that you've gotta leave. He's very unhappy, very angry, and I think he, He also blames her. He's trying to put up a good face, but it's a very bad thing in terms of a country when you do that. I'm not a fan of his, as you probably have noticed, and he had a rough debate, but that doesn't mean that you just take it away like that.” 

Trump can’t speak to Biden’s state of mind; all evidence is that Nancy Pelosi is perfectly sane – see her recent multiple rounds of interviews about her book, including with NPR ; again, Trump doesn’t know Biden’s state of mind; and again, nobody took it away.

47-51. “She's trying to say she had nothing to do with the border. She had everything. She was appointed to head the border. And then they said border czar. Oh, she loved that name. She loved that name. But she never went there. She went to a location once along the border, but that was a location that you would love to go and have dinner with your husband or whoever. That was a location that was not part of the problem. That was not really going to the border. So I– essentially she never went to the border.”

(1) As previously noted, she was not put in charge of the border and certainly did not have “everything” to do with it; (2) she was not appointed to head the border; (3) if “they” is the White House, then “they” did not call her “border czar”; (4) Trump doesn’t know what Harris might have thought about the term; (5) Harris did not go to a place at the border “you would love to go and have dinner with your husband or whoever.”

In 2021, Harris toured border patrol facilities in El Paso, Texas, visited an area where asylum seekers were screened, and met with migrants. Republicans criticized her at the time for not going to the Rio Grande Valley.

52. “Now we have the worst border in the history of the world.” 

World history is filled with cases where one country has crossed a border and invaded a neighboring country.

53. “She destroyed San Francisco. She destroyed California as the A.G. But as the D.A. She destroyed it. She– San Francisco. … She destroyed– no cash bail, weak on crime, uh, she's terrible.”

As San Francisco’s district attorney from 2004 to 2011, and then California’s attorney general until 2017, it’s true that Kamala Harris was deeply connected to how crime was prosecuted during that particular period. However, no single person is responsible for destroying any city or state, not to mention that both are not destroyed.

There are just too many factors that contribute to why crime rises and falls. What’s more, according to the FBI , both violent and property crime rates in California more or less mirrored national trends during her tenures. As a prosecutor, Harris was largely seen as aligning more with law-and-order tendencies, though she has supported some progressive reforms, like offering certain criminal defendants drug treatment instead of going to trial. She also tweeted support for a Minnesota bail fund after the 2020 protests of George Floyd’s murder. — Meg Anderson

During her campaign for the 2020 nomination, she rolled out a plan that would have phased out cash bail , and she pledged to eliminate it as president because “no one should have to sit in jail for days or even years because they don’t have the money to pay bail.” But in the same campaign, during a debate, former Hawaii Rep. Tulsi Gabbard criticized Harris for keeping cash bail in place as district attorney.

54. “And yet they weaponized the system against me.” 

The justice system was not weaponized against Trump. Biden went through pains to not show any interference with the Justice Department. And Trump was found guilty by a jury of his peers in New York in a state case.

55-58. “I won the big case in Florida. I won the big case. … Nobody even wrote about it. The big case.” 

(1) Trump did not “win” the classified documents case against him in Florida; (2) this was not “the big case” against him; (3) there was plenty of coverage of it; and (4) he goes on to repeat that he won the case later.

For context: the judge in the case controversially dismissed it, claiming the special counsel was unconstitutionally appointed despite Supreme Court decisions upholding independent counsels. The Justice Department has signaled it will appeal by the end of August but by the time the decision comes back, the election will be over.

Trump had four criminal cases against him including the classified documents case – the fraudulent business practices case in New York, for which he was convicted on 34 felony counts; an election interference case in Georgia; and the other federal case dealing with Jan. 6. If there was a biggest case, it was the last one.

59. “The judge was a brilliant judge, and all they do is they play the ref with the judges. But this judge was a fair but brilliant judge.”

There has been lots of criticism of the judge in the case, Aileen Cannon, who Trump appointed. She had very little experience as a trial judge, made several decisions that were questioned by legal experts and early in this case, had a ruling, in which she called for a special master to review classified documents first, overturned by the 11th Circuit.

60. “Now Biden lost it because he didn't have presidential immunity. He didn't have the Presidential Records Act. He lost it.”

This was not “Biden’s case.” It was to be tried by special counsel Jack Smith, who was appointed by Attorney General Merrick Garland. The Biden White House has made efforts to keep an arms-length distance from the investigation. Biden often declined to comment on the Justice Department’s and state investigations into Trump when it would likely have been politically advantageous for him to talk about it on the campaign trail.

61. “But the– I call it prosecutors, special counsel, special prosecutor to me. He–, appointed by him and appointed by Garland. He said the man's incompetent. He can't stand trial, but he can run for president.” 

This appears to be a misrepresentation of what special counsel Robert Hur said of Biden in a report he released investigating the president’s handling of classified documents. Hur said he wouldn’t be charging Biden, called the president “an elderly man with a poor memory" and said a jury might find sympathy with him because of it. He did not say Biden was incompetent and could not stand trial.

62. “She couldn't pass her bar exam.”

This is false. Harris passed her bar exam on the second try . She failed on first attempt, which is not unusual for California’s bar exam given its difficulty.

63. “I was doing very well with Black voters, and I still am. I seem to be doing very well with Black males. This is according to polls, as you know. 

Trump was not doing “very well” with Black voters. Biden was not doing as well with Black voters as he did in 2020, according to most surveys, but that didn’t mean Black voters were moving heavily toward Trump. Many seemed more likely not to vote. There were signs that Trump was doing better with Black men, but there wasn’t much good evidence to support this in polling, considering most national polls have such high margins of error with voter groups. A typical national survey might have 1,000 voters and 100 or so Black voters, give or take. That’s typically a margin of error upward of +/- 10 percentage points, meaning results could be a whopping 10 points higher or lower.

64. “Extremely well with Hispanic.”

Like with Black voters, it’s difficult to tell in most national surveys exactly how well a candidate is doing with Latino voters because of high margins of error. “Extremely well” depends on how it’s defined, but this is an exaggeration.

65. “Jewish voters, way up.”

Jewish voters traditionally vote roughly 2-to-1 for Democrats in presidential elections, so this seems more like a hope than reality.

66. “White males, way up. White males have gone through the roof. White males, way up.” 

It’s just not the case that Trump is “way up.” NPR polling finds that while Trump is doing as well as ever with white men without college degrees, Harris – and Biden before her – is actually leading with white men with college degrees, a group Trump won in 2020, according to exit polls .

67. “It could be that I'll be affected somewhat with Black females. Well, we're doing pretty well. And I think ultimately they'll like me better, because I'm gonna give them security, safety and jobs.”

Trump is not doing well with Black females. Black women are a key pillar Democratic voting group, and Black voters have moved more in Harris’ favor since she’s gotten in.

69. “We have a very bad economy right now. We could, we could literally be on the throes of a depression. Not recession, a Depression. And they can't have that. They can't have that.”

This is not the case. See earlier fact check. (He repeats this again later in the press conference, so it is included here in the count.)

70. “I know Josh Shapiro. He's a terrible guy. And he's not very popular with anybody.” 

A Fox News poll last month showed Pennsylvania Gov. Josh Shapiro, a finalist to be Harris’ running mate, had a 61% approval rating in the state. Other polls also found him with a net-positive rating, though, not quite as high.

71. “Listen, I had 107,000 people in New Jersey. You didn't report it.”

It was reported that the numbers come from faulty information about the size of a crowd at Trump’s rally. More accurate estimates appear to be anywhere from 30,000 to 60,000 . Still, a very large crowd, but Trump is exaggerating here.

72-77. “What did she have yesterday? 2,000 people? If I ever had 2,000 people, you'd say my campaign is finished. It's so dishonest, the press. … When she gets 1,500 people, and I saw it yesterday on ABC, which they said, ‘Oh, the crowd was so big.’ … I have 10 times, 20 times, 30 times the crowd size. And no, they never say the crowd was big. … I think it's so terrible when you say, ‘Well she has 1,500 people, 1,000 people,’ and they talk about, oh, the enthusiasm.” 

(1-3) Trump gave at least three incorrect estimates here, downplaying Harris’ crowd sizes (2,000, 1,500 and 1,000); (4) He also far overestimated how big his crowd sizes are compared to Harris’; (5-6) He twice said the press is dishonest about her crowd size and about his.

For context, the Harris campaign’s estimate was 10,000 or more at each rally. What the exact number is might be unclear — as is often the case with crowd-size estimates — but they were bigger than 2,000 and 1,500. Reporters have often commented on the size of Trump’s crowds. Frequently, they are very large, certainly larger than ones that Hillary Clinton drew in 2016 or Joe Biden this year, but Trump also regularly exaggerates their sizes.

78. “If I were president, you wouldn't have Russia and Ukraine, where it never happened. Zero chance. You wouldn't have had Oct. 7th of Israel.”

This is speculation, and that there is simply no way to know what would have happened in either case if he'd been reelected.

79. “You wouldn't have had inflation. You wouldn't have had any inflation because inflation was caused by their bad energy problems.” 

Again, this is speculative. Energy and food prices jumped sharply around the world following Russia’s invasion of Ukraine and the resulting sanctions on Russian energy. Gasoline prices in the U.S. hit a record high topping $5 a gallon. But domestic energy production has not suffered during the Biden administration. In fact, U.S. oil and natural gas production hit record highs last year. AAA reports the average price of gasoline today is $3.45/gallon. — Scott Horsley

80. "I don't know if you know, they're drilling now because they had to go back because gasoline was going up to $7, $8, $9 a barrel."

Oil and gas production has largely been determined by energy companies. They were disciplined about not expanding production when prices were low but have become more aggressive as prices climbed. While Kamala Harris opposed “fracking” for oil and gas during her 2019 presidential campaign, she now says she would not try to outlaw the practice – which is important in battleground states such as Pennsylvania. — Scott Horsley

81. “Everybody's going to be forced to buy an electric car, which they're not going to do because they don't want that. It's got a great market. It's got a market. It's really a sub market.”

The Biden administration has set a goal of having 50% of new vehicle sales be electric by 2030 . It has primarily tried to achieve this through carrots rather than sticks, offering incentives to make electric cars more affordable, encouraging the development of electric charging stations and using the federal government’s own purchasing power to create demand. — Scott Horsley

82. “We don't have enough electricity. We couldn't make enough electricity for that.”

A shift to electric vehicles will require a rapid updating and expansion of the U.S. power grid, according to the Electric Power Research Institute . However, as EVs become more efficient, the increased demand could be reduced by as much as 50% per mile traveled over the next three decades. — Scott Horsley

83. “The weight of a car, the weight of a truck, they want all trucks to be electric. Little things that a lot of people don't talk about. The weight of a truck is two-and-a-half times, two-and-a- half times heavier.” 

Electric vehicles are typically heavier than gasoline-powered vehicles, because of the batteries. But the weight difference is about 30% , not 250% as Trump said. What’s more, American vehicles have been getting heavier for decades, long before the move to EVs, thanks to the popularity of pickup trucks and SUVs.

84. “You would have to rebuild every bridge in this country, if you were going to do this ridiculous policy.”

While many bridges and other transportation infrastructure need improvement , the additional weight of EVs is just one of many factors that will need to be considered. Another challenge is that bridges and highways are typically funded through gasoline taxes. The shift to EVs, which don’t use gasoline, will require an alternate source of highway funding.

85-90. “So, but on crowd size in history, for any country, nobody's had crowds like I have, and you know that. And when she gets 1,000 people and everybody starts jumping, you know that if I had a thousand people would say, people would say, that's the end of his campaign. I have hundreds of thousands of people in, uh, South Carolina. I had 88,000 people in Alabama. I had 68,000 people. Nobody says about crowd size with me, but she has 1,000 people or 1,500 people, and they say, oh, the enthusiasm's back.”

There were at least six different misstatements here – (1) Trump has had large crowds, but “in history,” there certainly there have been people with larger crowds, from Barack Obama and others; (2, 3) her crowds have been larger than 1,000, which he repeats twice; (4) no serious analysts have said this is the end of Trump’s campaign. This race is very close; (5) there’s no evidence for crowds of the size Trump notes in South Carolina and Alabama; (6) people do talk about Trump’s crowd sizes.

91. “They wanna stop people from pouring into our country, from places unknown and from countries unknown from countries that nobody ever heard of.”

Someone has likely heard of whatever the unnamed country is.

92-93. “We're leading in Georgia by a lot. We're leading in Pennsylvania by a lot.”

The races in Georgia and Pennsylvania are within the margin of error, according to an average of the polls.

94. “So I won Alabama by a record. Nobody's ever gotten that many votes. I won South Carolina by a record. You don't win Alabama and South Carolina by records and lose Georgia. It doesn't happen.”

It does, and here’s why. Demographically, Georgia has become very different from South Carolina and Alabama. Georgia’s population is now majority-minority, according to the U.S. Census Bureau. Alabama and South Carolina are 64% and 63% white, respectively.

Georgia’s Black population is also significant politically — 33% of the state’s population is Black. By comparison, Alabama is 27% Black, South Carolina 26%. Latinos also make up 11% of Georgia’s population and Asian Americans are 5%, both of which are higher than Alabama and South Carolina. And Georgia’s population is marginally younger — 15% of Georgia’s population is older than 65% compared to 18% in Alabama and 19% in South Carolina.

95. “If we have honest elections in Georgia, if we have honest elections in Pennsylvania, We're gonna win them by a lot.”

Winning them by a lot is highly unlikely, considering how close the states have been in recent elections, but perhaps more pressing is Trump’s insinuation that there were voting problems in the two states, which there were not. That’s why Trump is upset with Republican Georgia Gov. Brian Kemp, for example, because he upheld the valid 2020 election results even in the face of pressure from Trump.

96. “Of course there'll be a peaceful transfer. And there was last time.”

This wholly ignores the Jan. 6 siege on the Capitol, which took place because of Trump’s election lies.

97. “Because I'm leading by a lot.”

Again, this is a very close race.

98. “We have commercials that are at a level I don't think that anybody's ever done before.”

This is false. Since Super Tuesday, Democrats have outspent Trump’s campaign and outside groups supporting him by more than double, according to data provided by AdImpact and analyzed by NPR — $373.5 million to $150.6 million.

99. “She's not smart enough to do a news conference.”

There is plenty of evidence that Harris is “smart enough to do a news conference,” as she has done in the past.

100. "We're in great danger of being in World War III. That could happen." 

Again, no serious analyst believes this.

101. “I think those people were treated very harshly, when you compare them to other things that took place in this country where a lot of people were killed.”

The Justice Department investigation into the events of Jan. 6, 2021, is the largest and most complex federal criminal probe in U.S. history, the attorney general has said. More than 140 law enforcement officers were injured that day, in what U.S. Attorney Matthew Graves has described as the biggest mass casualty event involving police. It’s hard to find any comparable event in recent American history.

As of Aug. 6, 2024, according to Graves’s office, prosecutors have charged more than 160 people with using a deadly or dangerous weapon or causing serious bodily injury to an officer. Prosecutors have also secured convictions on the rarely-deployed charge of seditious conspiracy, or attempting to overthrow the government by use of force, against top leaders of the Oath Keepers and the Proud Boys.

Even so, only a small number of Jan. 6 defendants have been held in federal custody while they await trial. Mostly, these are the rioters who allegedly used the most violence on that day more than three years ago. Republican members of Congress have toured the jail facilities and decried conditions there, expressions of support that defendants facing ordinary charges in D.C. have not received. — Carrie Johnson, NPR national justice correspondent

102. “Nobody was killed on Jan. 6th.” 

Conservatives were upset at the time that one of the rioters, Ashli Babbitt, was killed when she was shot by police, as she was trying to force her way into the Speaker’s Lobby of the Capitol, which leads to the House chamber, with a crowd of others. Many officers were injured that day; one died of a stroke as a result of Jan. 6; and others later died by suicide that their families say was also a result of Jan. 6.

103-105. “And, you know, it's very interesting, the biggest crowd I've ever spoken to. … The biggest crowd I've ever spoken before was that day. … The biggest crowd I've ever spoken. … I've spoken to the biggest crowds. Nobody's spoken to crowds bigger than me.” 

It was not the biggest crowd he’s ever spoken to. His inauguration would have topped that. And others have had bigger crowds, as noted earlier.

106. “I said peacefully and patriotically.”

While Trump did utter those words, it is misleading. Trump also said the word “fight” multiple times , and he told the already angry crowd because of the election lies he fed them: “We fight like Hell and if you don’t fight like Hell, you’re not going to have a country anymore.” Trump aides testified that he “refused” to tweet the word “peaceful” in the days leading up to the rally because he thought it might discourage people from being there, and he was concerned about his crowd size.

107-108. “If you look at Martin Luther King, when he did his speech, his great speech, and you look at ours, same real estate, same, everything, same number of people. If not, we had more. …You look at the picture of his crowd, my crowd, uh, we actually had more people.”

First, the speeches did not take place at the “same real estate.” Trump spoke from a position just south of the Ellipse. Martin Luther King Jr. spoke from the steps of the Lincoln Memorial

Second, the crowds were not the same size and Trump’s was certainly not larger. It is an extraordinary claim and shows just how much Trump cares about crowd size.

109. “We have a Constitution. It's a very important document, and we live by it. She has no votes.” 

Again, there’s nothing in the Constitution about how parties should pick their presidents.

110-111. “They said, ‘You're not going to win, you can't win, you're out.’ And at first they said it nicely, and he wasn't leaving, and then you, you know, the, you know it better than anybody. … At first, they were going to go out to another vote, they were going to go through a primary system, a quick primary system, which it would have to be. And then it all disappeared, and they just picked a person.”

As explained earlier, this is not how Biden wound up stepping aside. The story is yet another Trump invention. He also lies here in saying that “they were going to go through a primary system” and “it would have to be” a quick primary system.” There’s no requirement that a primary is held. In fact, for many years, candidates’ selection as party nominees had nothing to do with primaries, and they were not as prevalent as today.

112-113. “That was the first out. She was the first loser, OK? So, we call her the first loser. She was the first loser when– during the primary system, during the Democrat primary system, she was the first one to quit. And she quit.”

As explained earlier, Harris was not the first one out in the 2020 Democratic primary race. And “first loser” appears to be a name Trump made up at this news conference, as Harris has not been referred to that way as a result of her run for the 2020 nomination.

114. “She did, obviously, a bad job. She never made it to Iowa. Then for some reason, and I'm, I know he regrets it, you do too, uh, he picked her, and she turned on him too. She was working with the people that wanted him out."

Once again, this is a false conspiracy invented by Trump.

115. “She was the first one out.” 

Trump repeats this false line again.

116. “I think the abortion issue is written very much tempered down, and I've answered I think very well in the debate, and it seems to be much less of an issue, especially for those where they have the exceptions.”

Abortion rights as a political and social issue has certainly not “tempered down.” There are millions of women, especially across the South, who do not have access to abortion and women who have experienced pregnancy losses with the inability to access medications for those necessary procedures.

117. “As you know, and I think it's when I look for 52 years, they wanted to bring abortion back to the states. They wanted to get rid of Roe v. Wade and that's Democrats, Republicans, and Independents, and everybody. Liberals, conservatives, everybody wanted it back in the states. And I did that.”

Everybody absolutely did not want that. It was actually quite unpopular for the Supreme Court to overturn Roe . And he again repeats that it has become less of an issue.

118-119. “I think that abortion has become much less of an issue. It's a very small.” 

“I think it's actually going to be a very small issue. What I've done is I've done what every Democrat and every Every Republican wanted to have done.” 

“I think the abortion issue has been taken down many notches. I don't think it's of– I don't think it's a big factor anymore, really.”

Minutes apart from each other, he repeats these three false claims. Abortion rights is not a “very small” issue for millions of voters. Democrats are organizing around it, and it has been seminal to Biden and Harris’ campaigns.

120. “Previous to [Virginia Gov.] Glenn [Youngkin], the governor, he said the baby will be born, we will put the baby aside, and we will decide with the mother what we're going to do. In other words, whether or not we're going to kill the baby.”

This is a distortion Republicans continue to push about what former Virginia Gov. Ralph Northam said. This has been fact-checked by others multiple times .

121-122. “I think the abortion issue has been, uh, taken down many notches. I don't think it's of, uh, I don't think it's a big factor anymore, really.”

“Everybody wanted it in the states.”

“But that issue has is very much subdued.”

He once again returns to the issue of abortions, which remains a “factor,” not everybody wanted it in the states, the issue is not “very much subdued.”

123-124. “ She wants to take away everyone's gun.” 

Harris has not proposed taking away all guns. She has proposed banning assault-style weapons, something that was in place for a decade. Some surveys had shown majority support for this. Others show a split. (Trump makes this case later, as well, so that is also included in the count.)

125. “Some countries have actually gone the opposite way. They had very strong gun laws and now they have gone the opposite way, where they allowed people to have guns, where in one case they encouraged people to go out and get guns, and crime is down 29%.”

It’s difficult to compare gun violence and gun laws in the United States to other countries, simply because of the staggering amount of guns we have here. Although the U.S. has less than 5% of the world’s population, it holds almost 40% or more of the world’s civilian-owned guns. And it has “the highest homicide-by-firearm rate of the world’s most developed nations,” per the Council on Foreign Relations . Norway, Canada and Australia all tightened their gun restrictions after shootings. — Meg Anderson

126. “On July 4th, 117 people were shot and 17 died. The toughest gun laws in the United States are in the city of Chicago. You know that. They had 117 people shot. Afghanistan does not have that.” 

Though Trump didn’t get the numbers exactly right, Chicago did have an incredibly violent July 4th holiday weekend this year. According to Mayor Brandon Johnson, more than 100 people were shot and 19 of those people died. Chicago does have strict gun laws, in part because its state does: Everytown For Gun Safety, a nonprofit that advocates for gun control, ranks Illinois third in the nation for the strength of its gun-control laws. However, no state or city exists within a bubble, and Illinois is surrounded by states with much weaker laws, including Indiana, which is just a short drive from Chicago. — Meg Anderson

127. “For 18 months, not one American soldier was shot at or killed, but not even shot at.” 

This is, to put it charitably, misleading. It appears that he’s actually referencing the period when the Trump administration signed the deal with the Taliban, in advance of U.S. troops leaving. The deal said the U.S. would be out in 14 months, and in exchange the Taliban wouldn’t harbor terrorists and would stop attacking U.S. service members. Needless to say, the deal didn’t hold. But as the AP notes , “There was an 18-month stretch that saw no combat, or ‘hostile,’ deaths in Afghanistan: from early February 2020 to August 2021.” – Andrew Sussman

128. “Kamala is in favor of not giving Israel weapons. That's what I hear.”

Harris does not support an Israel weapons embargo. A Biden administration official posted on social media that Harris "has been clear: she will always ensure Israel is able to defend itself against Iran and Iran-backed terrorist groups.” A leader of the uncommitted movement said Harris “expressed an openness” to a meeting about an embargo, but the Biden administration official said Harris "will continue to work to protect civilians in Gaza and to uphold international humanitarian law,” not that she would support an embargo.

129. “She's been very, very bad to Israel, and she's been very bad and disrespectful to Jewish people.”

Harris’ husband, Doug Emhoff, is Jewish. The couple has hosted Passover Seders.

130. “Well, I know Willie Brown very well. In fact, I went down in a helicopter with him. We thought maybe this is the end. We were in a helicopter going to a certain location together and there was an emergency landing.”

This claim has not held up to scrutiny. Politico reported that Trump did have to make an emergency landing in a helicopter with a Black California politician decades ago, but it wasn’t Willie Brown, the former San Francisco mayor and state assembly speaker. It was Nate Holden, a former Los Angeles city councilman and state senator.

131-132. “This was not a pleasant landing, and Willie was— he was a little concerned. So I know him. I know him pretty well. I mean, I haven't seen him in years. But he told me terrible things about her.”

“He was not a fan of hers very much at that point.”

This is something Trump repeated twice, minutes apart from each other. Brown strongly denies having been on a helicopter with Trump or telling Trump negative things about Harris, whom he dated in the mid-1990s and supports now for president. The relationship ended in 1995.

133. “Our tax cuts, which are the biggest in history… .”

The 2017 tax cuts were not the biggest in history. As a share of the economy, they barely make the top 10 . They were big enough, however, to blow a big hole in the federal budget, which is why Trump was overseeing a nearly $1 trillion dollar annual deficit before the pandemic. — Scott Horsley

134. “It'll destroy the economy.”

This is what Trump said will happen if his tax cuts are not renewed. But The 2017 tax cut did not deliver the economic boom that its supporters promised, and there’s no reason to think reversing a portion of the cut would cause economic destruction. — Scott Horsley

135. “I've never seen people get elected by saying, 'We're going to give you a tax increase.'”

Vice President Harris has echoed President Biden’s pledge not to raise taxes on anyone making less than $400,000. However, Biden has called for raising taxes on wealthy individuals and raising the corporate tax rate from 21% to 28% – halfway back to where it was before the 2017 cut. — Scott Horsley

136. “These guys get up, think of it. ‘We're going to give you no security.’ …”

No Democratic presidential candidate has advocated “no security.”

137. “We're going to give you a weak military… .’ ”

An analysis by the American Enterprise Institute, a conservative think tank, showed a “review of historical defense budget trends shows there is more at play in determining overall investments in defense than just which party is in the White House.” Indeed, since the year 2000, U.S.-led wars overseas have resulted in a surge of spending by both Democratic and Republican administrations.

138-139. “…We're going to give you no walls, no borders, no anything.”

Harris, Walz and the Democratic Party have never said they want “no borders.” They certainly oppose Trump’s wall/fence along the entire U.S.-Mexico border, citing the exorbitant cost and its relative ineffectiveness, they say, compared to using other methods. (Trump later says that Harris wants “open borders,” so that’s included in the count here.)

140. “...We're going to give you a tax increase.”

Again, this is misleading and suggests Harris wants to increase taxes across the board when they have consistently talked about increasing taxes only on the wealthy. In Harris’ view, those making more than $400,000 a year .

141. “They're gonna destroy Social Security.”

Democrats have consistently advocated for keeping Social Security and making it solvent.

142. “They've weaponized government against me. Look at the Florida case. It was a totally weaponized case. All of these cases, by the way, the New York cases are totally controlled out of the Department of Justice. They sent their top person to the various places. They went to the A.G.'s office, got that one going, then he went to the D.A.'s office, got that one going, ran through it. No, no, this is all politics, and it's a disgrace.”

In congressional testimony this year, Attorney General Merrick Garland told lawmakers that President Biden had never called him to discuss any of the cases against Trump. Garland also had aides review Justice Department leaders’ email for any correspondence with Manhattan District Attorney Alvin Bragg. In a letter to Congress in June 2024, the Justice Department said it had found no such contacts.

In that same letter, Justice Department legislative affairs chief Carlos Uriarte said the department did not “dispatch” former acting Associate Attorney General Matthew Colangelo to New York to join Bragg’s team prosecuting Trump. “Department leadership was unaware of his work on the investigation and prosecution involving the former president until it was reported in the news,” Uriarte wrote. — Carrie Johnson

143. “Any time you have mail-in ballots, you're gonna have problems. ... We should have one-day voting; we should have paper ballots; we should have voter ID; and we should have proof of citizenship.” 

Trump continues to spread baseless claims about mail ballots. There’s no proof of widespread fraud with the voting method. When it comes to paper ballots, they're standard. One estimate found that in the 2024 general election, "nearly 99% of all registered voters will live in jurisdictions where they can cast a ballot with a paper record of the vote."

The proof of citizenship comment echoes a Republican push on the issue , though studies have shown voting by non-U.S. citizens in federal elections to be exceedingly rare. The GOP-led House has passed a bill to require such documentary proof, but it’s likely to go no further in a Senate led by Democrats who are opposed to adding new voting restrictions. — Ben Swasey, voting editor

144. “The polls have suggested, there are some polls that say we're going to win in a landslide.” 

There are no polls that suggest Trump will win in a landslide. By all accounts, this is a very close race.

145. “...they're paying 50, 60, 70 percent more for food than they did just a couple of years ago.”

The rise in grocery prices is a common complaint , but Trump exaggerates the scale of the increase. According to the Consumer Price Index, grocery prices have risen 25% since before the pandemic and 21% since President Biden took office. (At the same time, average wages have risen 23% since before the pandemic and 17% since President Biden took office.)

146-149. The Strategic National Reserve is “virtually empty now. We've never had it this low.”

“He's sucked all of the oil out.”

“Essentially the gasoline to keep the, to keep the price down a little bit. … But you know what? We have no strategic national reserves now. He's emptied it. It's almost empty. It's never been this low.”

“They've just, for the sake of getting some votes, for the sake of having gasoline–. You know, that's meant for wars. It's meant for, like, tragedy. It's not meant to keep a gasoline price down, so that somebody can vote for Biden or, in this case, Kamala.” 

The strategic oil reserve is actually up in the past year . Biden has since repurchased about 32 million barrels of oil for the Strategic Petroleum Reserve. As of this month, the reserve held about 376 million barrels of oil. The reserve was lower when Trump left office than when he got in.

150. “I see it right now, I see her going way down on the polls now.”

The opposite is true. Harris has continued her momentum since getting into the race.

151-152. “...now that people are finding out that she destroyed San Francisco, she destroyed the state of California.” 

As addressed earlier, Harris is not entirely responsible for San Francisco or the state of California. Crime trends there were similar to national crime trends during her time as district attorney in San Francisco and as the state’s attorney general. What’s more, preliminary data for this year indicates that many cities in California, including San Francisco, are seeing murder rates falling. (Trump repeats the claim one more time later in the news conference, so it is included in the count here.) — Meg Anderson

153. “She was early, I mean, she was the first of the prosecutors, really, you know, now you see Philadelphia, you see Los Angeles, you see New York, you see various people that are very bad, but she was the first of the bad prosecutors, she was early.”

Although Harris did refer to herself in her 2019 memoir as a “progressive prosecutor,” her legacy has largely been seen as tougher on crime. She has supported some progressive reforms, such as pretrial diversion, which offers certain criminal defendants things like drug treatment instead of going to trial. — Meg Anderson

154. “You know, with Hillary Clinton, I could have done things to her that would have made your head spin. I thought it was a very bad thing – take the wife of a president of the United States, and put her in jail. And then I see the way they treat me. That's the way it goes. But I was very protective of her. Nobody would understand that. But I was. I think my people understand it. They used to say, lock her up, lock her up. And I'd say, just relax, please.”

Trump called for Clinton’s imprisonment multiple times , including going along with crowd chants of “lock her up.”

155. “Don't forget, she got a subpoena from the United States Congress, and then after getting the subpoena, she destroyed everything that she was supposed to get. 

Clinton aides requested emails be deleted months before the subpoena, and the FBI said there’s no evidence the messages were deleted with a subpoena in mind. — Carrie Johnson

156. “I thought it was so bad to take her, and put her in jail, the wife of a president of the United States. And then, when it's my turn, nobody thinks that way.”

The Justice Department closed an investigation into Hillary Clinton’s use of a private email server to conduct some State Department business in 2016. Then-FBI Director Jim Comey gave a press conference to explain his reasoning in July of that election year. Comey said, “We did not find clear evidence that Secretary Clinton or her colleagues intended to violate laws governing the handling of classified information,” but he criticized Clinton and her aides for being “extremely careless in their handling of very sensitive, highly classified information” that flowed through the server.

By contrast, prosecutors in the Florida case against former President Donald Trump said Trump had flouted requests from the FBI and a subpoena for highly classified materials he stored in unsecure spaces like a ballroom and a bathroom at his Mar-a-Lago resort. The indictment in that case accuses Trump of unlawfully retaining government secrets and of intentionally obstructing justice with the help of an aide who moved boxes of materials and otherwise allegedly thwarted the FBI probe. Trump and his co-defendants pleaded not guilty. The Justice Department says it is appealing the district court’s decision to toss the case on constitutional grounds. — Carrie Johnson

157. “A lot of the MAGA, as they call them, but the base. And I think the base is, I think the base is 75% of the country, far beyond the Republican Party.”

Rounding up, Trump won 46% of the vote in 2016 and 47% of the vote in 2020. He has a high floor, but a low ceiling politically. Majorities continue to say they have an unfavorable rating of Trump, which has been consistent for years. No American presidential candidate has ever gotten 75% of the vote in this country, dating back to 1824 since data was kept for popular votes. Lyndon B. Johnson got 61% in 1964, Richard Nixon slightly less than 61% in 1972, Ronald Reagan 59% in 1984. Since then, Barack Obama got nearly 53% in 2008 and 51% in 2012, the first candidate since Eisenhower to win at least 51% of the vote twice.

158. “My sons are members, and I guess indirectly I'm a member, too.”

Trump here is talking about membership in the National Rifle Association. Another family member being an NRA member does not make someone else an NRA member “indirectly.”

159. “She served 24 years for being on a phone call having to do with drugs. You know who I'm talking about. She was great. And she had another 24 years to go. And it was largely about marijuana, which in many cases is now legalized, OK?”

Presumably, Trump is talking about Alice Marie Johnson, who had been convicted on cocaine conspiracy and money laundering charges . Kim Kardashian advocated for Johnson and won a pardon for her from Trump.

160. “They're either really stupid, and I don't believe they're stupid, because anybody that can cheat in elections like they cheat is not stupid.”

More than 60 court cases proved there was not widespread fraud or cheating that would have made any difference in any state.

161. “Lately I've seen where they're trying to sign these people up to vote. And they have to stop. They cannot let illegal immigrants vote in this upcoming election.”

This is a conspiracy not based in fact. Immigrants in the country illegally cannot vote in presidential elections, and there’s no evidence there is an intentional effort to sign them up in mass numbers to sway elections.

162. “If you go to California, and you ask the people of California, do they like the idea of sanctuary cities? They don't like it.”

The subject of sanctuary cities actually mostly splits Californians. Slim majorities have actually said that they favor the sanctuary-state law and are against their cities opting out of the law. Of course, this breaks down along party lines, and since California is heavily Democratic, those results might not be surprising. But it’s more divided than Trump suggests.

• 2024 presidential election

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Graduate Data Analyst CV layout and format

Your CV is the first impression you’ll make on anybody who reads it.

A disorganised, cluttered and barely-readable CV could seriously decrease your chances of landing interviews, so it’s essential to make sure yours is slick, professional and easy to navigate.

You can do this by using a clear structure and formatting your content with some savvy formatting techniques – check them out below:

Tips for formatting your Graduate Data Analyst CV

• Length: If you want to hold the reader’s attention and ensure your CV isn’t yawn-worthy, it’s best to stick to two sides of A4 or less. This is more than enough room to highlight why you’re a good match for the role – anything more can quickly become tedious!
• Readability : To help recruiters quickly skim through your CV, it’s important to format your section headings with bold or a different colour font and break up lengthy paragraphs into short sharp bullet points. This enables them to easily identify important information and assess your suitability.
• Design: When it comes to CV design, it’s best to keep things simple and sleek. While elaborate designs certainly command attention, it’s not always for the right reasons! Readability is key, so whatever you choose to do, make sure you prioritise readability above everything.
• Photos: Don’t add profile photos to your CV unless you work in an industry or region which prefers to see them. Most employers in the UK will not need to see one.

Quick tip: Creating a professional CV style can be difficult and time-consuming when using Microsoft Word or Google Docs. To create a winning CV quickly, try our quick-and-easy CV Builder and use one of their eye-catching professional CV templates.

CV structure

For easy reading, write your CV to the following CV structure:

• Contact details – Make it easy for recruiters to get in touch with you by listing your contact details at the top of your CV.
• Profile – A short and snappy summary of your experience and skills, showcasing what makes you a good fit for the position.
• Work experience / career history – Note down all your work history, with your current position first, then working backwards.
• Education – A short list of your academic background and professional/vocational qualifications.
• Interest and hobbies – This is an optional section, which you can use to highlight any relevant hobbies or interests.

Now you understand the basic layout of a CV, here’s what you should include in each section of yours.

Contact Details

Tuck your contact details into the corner of your CV, so that they don’t take up too much space. Stick to the basic details, such as:

• Mobile number
• Email address – It should sound professional, such as your full name.
• Location -Just write your rough location, rather than your full address.
• LinkedIn profile or portfolio URL – If you include these, ensure they’re sleek, professional and up-to-date.

Graduate Data Analyst CV Profile

Make a strong first impression with recruiters by starting your CV with an impactful profile (or personal statement for junior applicants).

This short introduction paragraph should summarise your skills, experience, and knowledge, highlighting your suitability for the job.

It should be compelling enough to encourage recruiters to read through the rest of your CV.

CV profile writing tips:

• Make it short and sharp: When it comes to CV profile length, less is more, as recruiters are often time-strapped. Aim for around of 3-5 persuasive lines.
• Tailor it: Before writing your CV, make sure to do some research. Figure out exactly what your desired employers are looking for and make sure that you are making those requirements prominent in your CV profile, and throughout.
• Don’t add an objective: Career goals and objectives are best suited to your cover letter , so don’t waste space with them in your CV profile.
• Avoid generic phrases: Clichés like “ blue-sky thinker with a go-getter attitude” might sound impressive to you, but they don’t actually tell the recruiter much about you. Concentrate on highlighting hard facts and skills, as recruiters are more likely to take these on board.

Example CV profile for Graduate Data Analyst

What to include in your graduate data analyst cv profile.

• Experience overview: Start with a brief summary of your relevant experience so far. How many years experience do you have? What type of companies have you worked for? What industries/sectors have you worked in? What are your specialisms?
• Targeted skills: Ensure that your profile highlights your key skills that are most relevant to your Graduate Data Analyst, and tailor them to match the specific job you are applying for. To do this, refer to the job description to closely align your skills with their requirements.
• Key qualifications: Be sure to outline your relevant Graduate Data Analyst qualifications, so that anyone reading the CV can instantly see you are qualified for the jobs you are applying to.

Quick tip: If you are finding it difficult to write an attention-grabbing CV profile, choose from hundreds of pre-written profiles across all industries, and add one to your CV with one click in our quick-and-easy CV Builder . All profiles are written by recruitment experts and easily tailored to suit your unique skillset.

Core skills section

Create a core skills section underneath your profile to spotlight your most in-demand skills and grab the attention of readers.

This section should feature 2-3 columns of bullet points that emphasise your applicable skills for your target jobs. Before constructing this section, review the job description and compile a list of any specific skills, specialisms, or knowledge required.

Important skills for your Graduate Data Analyst CV

Data analysis – Collecting, organising, and analysing complex data sets using statistical methods and data visualisation tools.

Programming – Utilising knowledge of programming languages such as Python, R, and SQL to process and manipulate data.

Problem resolution – Identifying and troubleshooting issues in data sets and developing solutions to improve data quality and accuracy.

Stakeholder communication – Explaining complex data analysis concepts in simple and understandable language to both technical and non-technical stakeholders.

Data management – Utilising knowledge of data warehousing, data integration, and data migration to ensure data accuracy and accessibility.

Machine learning – Utilising knowledge of machine learning algorithms and techniques to build predictive models and identify trends in data.

Excel proficiency – Utilising Microsoft Excel to manipulate and analyse large data sets and create charts and graphs for presentations.

Statistical analysis – Utilising knowledge statistical software such as SPSS, SAS, and STATA to perform statistical analysis and create regression models.

Data visualisation – Utilising knowledge of data visualisation tools such as Tableau, Power BI, and QlikView to create compelling and informative visualizations of data.

Project management – Managing projects, prioritising tasks, and meeting deadlines while ensuring high quality and accuracy of work.

Quick tip: Our quick-and-easy CV Builder has thousands of in-demand skills for all industries and professions, that can be added to your CV in seconds – This will save you time and ensure you get noticed by recruiters.

Work experience section

Now that recruiters have a good overview of your skills and abilities, you need to jump into the detail of your career history.

Give them a more thorough insight into what you can do by creating a detailed list of your relevant experience.

Start with your current role, and work backwards through all the relevant positions you’ve held. This could be freelance, contract or voluntary work too; as long as it’s related to the role you’re applying for.

Structuring each job

Lengthy, unbroken chunks of text is a recruiters worst nightmare, but your work experience section can easily end up looking like that if you are not careful.

To avoid this, use my tried-and-tested 3-step structure, as illustrated below:

Begin with a summary of your role, detailing what the purpose of your job was, who you reported to and what size of team you were part of (or led).

Key responsibilities

Follow with a snappy list of bullet points, detailing your daily duties and responsibilities.

Tailor it to the role you’re applying for by mentioning how you put the target employer’s desired hard skills and knowledge to use in this role.

Key achievements

Finish off by showcasing 1-3 key achievements made within the role.

This could be anything that had a positive effect on your company, clients or customers, such as saving time or money, receiving exemplary feedback or receiving an award.

Sample job description for Graduate Data Analyst CV

Internship at Intel, a world leader in the design and manufacturing of essential technologies that power the cloud and an increasingly smart, connected world. Working within the The Data Center & Artificial Intelligence Group (DCAI) further developing professional experience in advanced data intelligence and improving skills in this area.

Key Responsibilities

• Designing and building scalable and effective data models
• Enabling and implementing the advanced analytics capabilities into reports for analysis
• Responsible for profiling, cleaning and transforming data
• Working with stakeholders to identify data and reporting requirements and then turning raw data into relevant and meaningful insights

Quick tip: Create impressive job descriptions easily in our quick-and-easy CV Builder by adding pre-written job phrases for every industry and career stage.

Education and qualifications

In your education section, make any degrees, qualifications or training which are relevant to Graduate Data Analyst roles a focal point.

As well as mentioning the name of the organisation, qualification titles and dates of study, you should showcase any particularly relevant modules, assignments or projects.

Hobbies and interests

The hobbies and interests CV section isn’t mandatory, so don’t worry if you’re out of room by this point.

However, if you have an interesting hobby , or an interest that could make you seem more suitable for the role, then certainly think about adding.

Be careful what you include though… Only consider hobbies that exhibit skills that are required for roles as a Graduate Data Analyst, or transferable workplace skills.

There is never any need to tell employers that you like to watch TV and eat out.

A strong, compelling CV is essential to get noticed and land interviews with the best employers.

To ensure your CV stands out from the competition, make sure to tailor it to your target role and pack it with sector-specific skills and results.

Remember to triple-check for spelling and grammar errors before hitting send.

Good luck with the job search!