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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

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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• Data Analyst Resume Example
• Entry Level Data Analyst Resume Example
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• Experienced Data Analyst Resume Example
• Junior Data Analyst Resume Example
• Healthcare Data Analyst Resume Example
• Business Data Analyst Resume Example
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• Tips for Data Analyst Resumes
• 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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24 Data Analyst Resume Examples for 2024

Data Analyst Resume

• Data Analyst Resumes by Experience
• Data Analyst Resumes by Role
• Writing Your Data Analyst Resume

The number of data analysts is expected to  grow by 25 percent  between 2020 to 2030, coupled with the  increase in pay transparency laws  making this the ideal time to get a data analyst job.

Fun fact: before starting BeamJobs, one of our founders worked as a data analyst for six years. With his guidance, we’ve reviewed many data analyst resumes to figure out what helps data analysts get more interviews.

Building your resume  and  data analyst cover letter  is the hardest part of this process. To inspire you, we chose  24 top data analyst resume samples  for different career stages.

Our data analyst resume examples are proven to help you put your best foot forward to get the job you’ve always wanted in 2024.

or download as PDF

Why this resume works

• Once you know what the employers are looking for, you can include directly applicable keywords and matching language in your work experience bullet points (provided the keywords truly describe you!)
• After you’ve determined the content and matching keywords for your bullet points, add in any quantifiable metrics that can showcase your experience and help prove your merit.

Data Analyst Intern Resume

• If you lack paid work experience in a field, consider it an opportunity to include personal projects on your data analyst intern resume where you demonstrated skills relevant to the position you’re applying to.

Entry-Level Data Analyst Resume

• Unsure how to  start a resume ? No problem! Start by using a  solid resume outline  to help you get a feel for what a resume looks like, then add your experience and skills one at a time.
• The first is to demonstrate programming, testing, modeling, and data visualization competency by building well-designed projects that solve real problems through code.
• The key here isn’t reinventing the wheel but creating something dynamic and unique that can’t be easily replicated with a few Google searches and a video tutorial.
• The second option is to invest time and effort into internships. They’re a fantastic way for an aspiring degree-holder to gain on-the-job experience.
• Some internships require a completed degree before starting. Although this is becoming more uncommon due to online coding trade schools, do some research regarding markets and locations.

Entry-Level Risk Adjustment Data Analyst Resume

• To impress hiring managers, include programming languages you’re familiar with, what you hope to do at your future job, and some of your passions within the field.
• The first is to build well-designed scalable projects that solve real problems through code. So, if you haven’t done any projects, now’s the time to start! Projects are a great way to fill your resume if you don’t have work experience.
• The second option is to get an internship. Some internships require a degree, but online coding trade schools and boot camps are becoming more popular and feasible.

Junior Data Analyst Resume

• Even when a project wasn’t part of a previous job, be as specific as you can by including examples or metrics to show your impact! 
• Ensure that any projects or accomplishments such as internships, classes, or volunteer initiatives, relate directly to the job role. 
• Including a career objective  can also help bulk up your resume with information about what you can offer. 
• Examples and quantifiable metrics of success can make any resume outshine the competition: And they’re extra important for junior data analysts! 
• Since data analysis focuses so heavily on numbers like profits and improvement percentages, include plenty of these to back your credibility. 

Senior Data Analyst Resume

• Highlight a lengthy career in data analyst roles with quantifiable data from multiple sources, jobs, leadership, and mentoring.
• Only include highly relevant ones like Python, SQL, Tableau, and Excel with additional modeling, data visualization, and product analytics keywords.

Senior Insurance Data Analyst Resume

• Including a  resume summary  on your senior insurance data analyst resume helps you highlight your lengthy career with quantifiable data from various sources and can help you land an interview by setting you apart from more novice competition!
• This  resume format  allows the employer to read your work history like an unfolding story, but with the punchline first.
• Only list  skills on your resume  that truly apply to the role at hand; you’ve got limited space—don’t waste it.

Data Governance Analyst   Resume

• For your case, achievements that touch on cutting costs (cue:  saving 13% in infrastructure expenses ) and reducing process times (cue:  saving 12 hours per week ) would propel your candidacy to early success.

Data Quality Analyst Resume

• Therefore, to have a soft landing for your application, don’t spare any skills that you feel are relevant to the job—either in your resume or letting an AI cover letter generator have a go at your application. Including your mastery in Talend Data Quality, QuerySurge, Informatica Data Quality, and more would be a great strategy to impress potential employers.

Financial Data Analyst   Resume

• List down the best financial institutions like Citi and Deloitte that you’ve worked for (even for a position as low as an intern or volunteer!) and you’ll be on every employer’s hiring list. It’s also a great idea to list any certifications you hold such as “Chartered Financial Analyst.”

R Data Analyst Resume

• Follow John’s lead and state how you’ve worked with data and specifically (very important!) on R-based frameworks. Keep things simple and vary how you’ve helped each company during your tenure.

Alteryx Data Analyst   Resume

• For instance, rather than simply listing your proficiency in data manipulation, describe how you leveraged your expertise in this area to free up storage space and increase efficiency for the organization.

Big Data Analyst Resume

• Take your big data analyst resume to the next level by demonstrating your prowess in presenting actionable analyses to key organizational stakeholders.

Clinical Data Analyst Resume

• Even a candidate with years of industry experience can optimize their clinical data analyst resume with an additional certification. Make sure recruiters can easily spot that you’re a Certified Clinical Data Analyst (CCDA) to add an extra level of credibility to your background.

Creative Data Analyst Resume

• This will demonstrate to hiring managers that you bring a fresh perspective to the table—always a plus on a creative data analyst resume!

Lead Data Analyst Resume

• Formatting your resume  in reverse-chronological order is always a good way to wow recruiters with your most recent experience and relevant accomplishments. Put your best foot forward!
• Make sure your examples of leading roles are also as well-rounded as possible since this is another quick way to demonstrate how much you’ve learned throughout your career. 
• Since lead data analyst roles are so focused on details and critical thinking, make sure you highlight these areas, too! 
• Use solid, quantifiable metrics like improvement rates and dollar-amount company savings to back up your achievements. 

Healthcare Data Analyst Resume

• For instance, if you’ve completed a B.S. in Health Care Informatics, it means you’ve spent an extensive period of time learning how to analyze and interpret healthcare data and information—which is what most recruiters will be looking for in your healthcare data analyst resume .

Business Data Analyst Resume

• By doing so, you put your most recent accomplishments at the very top of your business data analyst resume —which is where a recruiter or your next potential employer is going to look first.

Marketing Data Analyst Resume

• For instance, if you’ve completed a Professional Certified Marketer (PCM) certification, it’s clear you understand the nuances required to be a marketing professional. Then, you can use the work experience bullet points to focus on the analysis aspect of your role.

AWS Data Analyst Resume

• You only have a couple of sentences to do so, but it’s still a powerful way to tell a recruiter exactly what you bring to the table and what they stand to gain if they hire you.

SQL Data Analyst Resume

• Start by analyzing the requirements in  data analyst job descriptions  to get an idea of what employers require.
• Speak with your current manager if you’re anxious about changing position titles. Always err on the side of caution, and ask for permission instead of forgiveness.

Data Analytics Manager Resume

• Making your resume easy to read  can be as simple as using a  resume template , but it also means  condensing your bullet points as much as you can ,  including metrics  to boost your credibility quickly, and leaving just enough white space to make it a breeze to skim.
• The first is the job description’s list of required skills. The second source is a job board advertising analytics manager roles in a specific geographic location. 
• Both sources give you a general idea of what you need to emphasize in your bullet points and what KPIs to use to complement your experience.

Revenue Reporting Data Analyst Resume

• Your resume should be formulated specifically to target the list of requirements from the company  job description . 
• Use our  resume checker  and a spellcheck extension (like Grammarly) to ensure your resume is error-free.

Data Analyst/Finance Analytics Resume

• Including numbers and percentages is the fastest way to show employers your qualifications. Use metrics to show how you’ve made significant improvements whenever you can.
• Using professional yet stylish  resume templates  and  resume outlines  equips you to add sections specifically for certificates and licenses.
• Don’t be afraid to use a hint of modest color to enhance the overall look of your resume. You’re a pro with personality after all!

Related resume guides

• Data Science Resume
• Financial Analyst
• Computer Science
• Data Engineer

Data Analyst Resume Guide for 2024

According to the  U.S. Bureau of Labor Statistics , the employment of computer and information research scientists (including data analysts) is projected to grow 16 percent from 2018 to 2028. This is much faster than the average for other jobs!

Due to the high demand and high wages, it makes sense that people are flocking to apply for data analyst roles.

But that doesn’t mean you should be discouraged. Applying online to jobs can feel like applying in a black hole, and we know it sucks.  It took one of our founders 77 job applications  before he landed his first data analyst job at Geico, and the next job was much easier to get.

One issue with applying for data analytics roles is that these titles are not standardized across different companies. At one company, data analysts might spend their time building reports in Tableau, while at another, they might be writing machine learning models for production.

Because of this variability, it can be tough to be sure to include the correct information in your data analytics resume. With this guide, you’ll put your best foot forward, no matter which data analyst roles you’re seeking!

Show off your data analyst skills

First, you need to show you have the right abilities for the job! This means you need to accomplish two goals with the  skills section of your data analyst resume . First, you have to be able to get past the automatic keyword filters in the applicant tracking system (ATS), which companies use to filter applicants. Next, you want to demonstrate your technical proficiency to the person reviewing your resume.

If you’re unsure which skills to include, we analyzed the data to learn  which skills are most in demand for companies hiring data analysts .

These two goals are, unfortunately, mostly in opposition to each other. If your goal was to just get past the ATS, you’d list every skill to get your foot in the door:

Bad — avoid a long list of generic skills

The problem? This method is a big red flag to technical hiring managers. You should only include skills you’d be comfortable discussing in your  data analyst interview . Plus, your  skills section shouldn’t take up more than 20 percent  of the page.

Any reasonable employer won’t expect you to know SAS, R,  and  Python. Instead, just list the technical skills that you’ve coded in before. And avoid including a skill like “data mining” or “data analysis” since a technical hiring manager knows these are just blanket terms that don’t mean much. Instead of “data mining,” list actual techniques you’ve used, like “decision trees” or “logistic regressions.”

But even when narrowing it down, sometimes your skills list looks cluttered and hard to read. Never fear; there are multiple ways to organize your skills section! For starters, you can list your skills by how proficient you are with them (“Advanced” vs. “Familiar,” for example). Alternatively, you can list your skills by skill type. You can even mention the years of experience you have with each tool.

For programming languages, mention the libraries and frameworks you use for data visualization and manipulation in that programming language.

Good—specific skills and modeling techniques

Your data analyst objective

Most of the time, you don’t need to include a  resume objective  or  resume summary ; a mistake many data analysts make. If a resume summary or objective doesn’t add value to your application, it’s okay to leave it out.

Here’s a sample data analyst resume objective that you would want to leave off of your resume:

Bad—uninformative resume objective

Why leave this off? It’s redundant. Suppose you already demonstrate in your resume that you used tools like Python and SQL to turn data into actionable insights. In that case, your objective doesn’t tell the person reviewing your resume any new information.

When to include a resume objective

• You’re undergoing a career change. You can say something like, “After 4 years of working in operations, I am now looking to leverage my expertise in turning data into insights as a data analyst.”
• You have a specific interest in a given role or company that makes you an especially strong candidate. For example, “Reading Match.com’s data blog ignited my pursuit of a career in data analytics, and I want to further contribute to the data-driven culture at the company.”

Summaries are similar, but they’re for candidates with over 10 years of experience and can include more personal achievements. There isn’t much difference between a resume summary or an objective; all you need to know is when you should include them.

Data analyst resume format

Here are some quick tips for formatting your data analytics resume:

• Keep it to one page.
• Break up bullet points into small, consumable pieces of information.
• Don’t refer to yourself with “I” or “we,” as it takes up room and looks unprofessional.
• Double, triple, and quadruple-check your grammar and spelling. One error can send your resume into the “no” pile!
• Each bullet point on your resume should be a self-contained, complete thought.

When a hiring manager reviews 50+ resumes for a given role, they quickly look for reasons to say “no.” By using these  resume-formatting tips , you make it easier for the hiring manager to see your worth and ask you for an interview, getting you one step closer to a job. 

Contact information

Of all the places to make an error, your contact information is the  worst  place to have it happen. One of our team members recounted their early days out of college as a data analyst. When they were applying for jobs, they accidentally wrote the wrong email address on their resume for seven different positions.

Even if they were perfectly qualified for the role, there was no way to contact them because of a minor mistake. So believe us when we say you need to  triple-check this section for any spelling, grammar, or link errors .

As part of your contact information, you should include your name and the role you’re applying for (even if it’s not your current role).

You don’t need to include your full address in this section, but you should list your city and zip code. You also need your phone number just in case your employer prefers that method.

Finally, include a link to your LinkedIn profile and anything else that might convey why you’re a great data analyst. If you have an active Github, include a link to that. If you do a lot of Kaggle contests, include a link to your profile. Have a personal blog where you talk about election data? Be sure to include a link.

Data analyst projects for your resume

If you’re entry-level and looking for your first full-time role, including projects on your data analyst resume is an absolute must. However, the more work experience you get, the more projects should become less critical. By the time you have four-plus years of experience in the field, you should only include a project of which you’re exceptionally proud.

What projects should you list? Anything where you identified (or were given) a problem and you used data to come up with an answer to that problem. It’s okay if it’s a class project, but it’s even better if you took the initiative yourself.

If you don’t have any such projects, now is the time to work on some. Do you have a question you’ve never answered? An experiment you’ve been longing to try? Think of a way to gather and analyze data to sate your curiosity.

Here’s an example: one of our founders had a hunch that the major job boards (Indeed, Glassdoor, and LinkedIn) essentially had the same jobs for data science roles. So, he manually collected data, analyzed it, and wrote about it to determine the  best job board for data scientists .

The projects you include don’t need to be exhaustive or ground-breaking. Employers just want to see that you can ask a question, use data to answer it, and present your findings reasonably and clearly.

Good—show you can answer your own questions with data

When talking about your projects, here’s how you should frame what you did:

• Clearly state the question you were answering or the problem you were trying to solve
• Show what tools or languages you used to solve the problem
• State the impact of the work you did

Your projects section is also an opportunity to provide more context around the programming languages and libraries you listed in your “skills” section. 

Like the “projects” section, the education section of your resume will be longer for entry-level data analysts relative to more experienced data analysts. You’ll want to include relevant courses you took in school related to data analytics for entry-level data analysts.

Courses relevant to data analytics are any mathematics, statistics, programming, and economics classes you took. To be an effective data analyst, you need to apply the principles you learned in these classes to real-world problems and datasets.

For entry-level roles, include relevant classes you took in school

Regardless of your experience level, you should always mention the school you attended, what you majored in (including minors or certifications), and when you graduated. This would also be the place to list any boot camps or relevant online courses you may have taken in the field.

If your background is in academia, you can also list any publications you may have co-authored. Be sure to include the title of the magazine and a link to allow the hiring manager to read further if they’re interested.

Only mention your GPA on your resume if it’s something you want to highlight—generally, only list your GPA if you’re entry-level and obtained anything above a 3.0.

Work experience

You analyze data for a living, so you know that numbers count when it comes to information. So when you’re talking about your work experience, your goal should be to highlight your accomplishments using numbers and estimates.

The formula for talking about work experience

“Specific contribution to project mentioning specific tools and skills”

“quantitative impact of the project”

“Performed a customer cohort analysis using SQL and Excel and recommended an email campaign for one customer segment”

“that lifted monthly retention by 10%”

Enter your text here…

When discussing your work, especially if it was a team project, emphasize your specific contributions. For example, you may have made a product recommendation based on a previous analysis. You’d want to talk about that particular recommendation on your resume instead of the built feature.

When talking about the quantitative impact, it’s okay to talk about the project as a whole. Following the example above, it’d be impossible to tease out the value of your product recommendation versus the engineer’s impact who built the feature since it’s a team effort. You’d say the feature had a revenue impact of $X on your resume.

Data analysts work across many different teams and projects in a company, so it’s not always easy to tie your work to a revenue impact. Still, try estimating your contributions using metrics to make your resume stand out.

These can be very rough estimates; you just want to make it clear that you’ve contributed to positive outcomes for the businesses where you worked.

Ways to quantify the impact of your analytics work

• “Used Python and SQL to determine a specific change in the landing page, resulting in a 10% boost in free trial activation rate”
• “Streamlined and automated a key business report in Tableau, saving the team 10 hours of reporting each week”
• “Used SQL and Excel to recommend ending contracts with worst-performing vendors, resulting in a costs savings of $100,000 annually”
• “Built data visualizations in Excel to demonstrate the efficacy of marketing plan, resulting in the close of a $1.3M Series A”
• “Determined through analysis in Python that emailing customers who had been inactive for 7 days resulted in a retention improvement of 7 basis points”
• “Identified procedural areas of improvement in hiring data to improve the time-to-hire for key roles by 11 days”
• “Used SQL and Excel to identify common complaints amongst new customers, leading to changes that improved new customer satisfaction by 14%”

When formatting your work experience, always list your most recent work at the top of your resume and list your other positions in reverse-chronological order.

Just to hammer home our point even further, here’s an example of the same work experience. One is stated in a quantitative impact, and one is not. 

Bad—no quantitative impact

Good—quantitative impact

Tailor your resume for each job

For each role to which you apply,  make minor edits to your resume  based on the  data analyst job description . Fortunately, you don’t have to completely rewrite your resume; just a few tweaks will do.

For example, let’s say you’ve done projects in both Python and R, and your resume heavily leans into your Python experience. If you apply to a job that mentions R, you should change your resume to discuss your R experience.

Similarly, if you have specific projects that relate to the job you’re applying for, include those projects. If you’re applying for a marketing data analyst role and have experience building marketing mix models, your application will become significantly stronger by mentioning those mix models.

Let’s say you’re applying to this job:

This seems like a heavy data visualization role. Instead of mentioning predictive modeling, talk extensively about your experience building robust data visualization in Tableau.

Change this:

How to Write an Effective Data Analyst Resume

Here are the major takeaways you should keep in mind when  writing a professional resume :

• Keep it to one page and  proofread, proofread, proofread .
• Otherwise, don’t let your education section take up a lot of space.
• You don’t need a summary or objective section on your resume unless you’re undergoing a career change or have over 10 years of experience.
• Only include skills on your resume for which you’d be comfortable being interviewed.
• Mention your specific contributions and quantify the overall project’s impact on the business.

By following this guide, you’ll be able to quickly and convincingly make the case that you’re a great fit for the data analyst role for which you’re applying. 

Applying for jobs isn’t easy, but you’ve taken a huge first step toward landing that dream job. Now all that’s left is to write,  double-check your resume  for errors, and submit it to your dream job!

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.

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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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• • Cofounded and lead the company in Italy with a mission to bring the experience of watching space objects to masses.
• • Showed the Moon and planets via telescopes to 5000+ people.
• • Developed a web-base feedback tool for designers and developers (Python, NodeJs, Javascript/React). Lead a team of 2 developers.
• • Acquired 10000+ registered, 1500+ active, and 50+ paying users.
• • Introduced hybrid context-based music recommender (accepted to ICML2017 workshop on Machine Learning for Music Discovery).
• • Surveyed human aided bots (in review at IEEE Internet Computing), and introduced a way such bots could be used in city context (accepted to RecSys2017 workshop on Recommender Systems for Citizens). Currently, I design and develop a chatbot able to self-learn new skills (to submit to WWW2018), and techniques to generate data via crowdsourcing for training NLU models (to submit to CHI2018).
• • Developed techniques to predict the quality of results in crowd platforms based on workers behavior (to submit to WWW2018).​
• • Published in CSCW2016, Internet Computing, HCOMP2015, Transactions on the Web, BPM2015, AVI2014, CHItaly2013, BPMS2012.
• • Together with colleagues from Milan, Sydney, and Zabol we made the most extensive review of quality assurance and assessment techniques in crowdsourcing (in review at ACM Computing Surveys).
• • Conducted a user study about task searching (published in AVI2014).
• • Developed a prototype of task listing page, designed for optimising task searching experience. It was partially adopted in production.
• • MUSIC RECOMMENDATION (rich-context-based music recommender system, crowdsourcing-based music tagging solution)
• • NLU and CONVERSATIONAL AGENTS (training data generation for NLU with crowdsourcing, NLU retraining techniques, Human Aided Bots, self-learning chatbots)
• • CROWDSOURCING (Ph.D. in quality control in crowdsourcing, internship at CrowdFlower)
• • USER STUDIES (performed multiple studies analysing workers' behaviour on Amazon Mechanical TURK and CrowdFlower)
• • SURVEYS (conducted various surveys, including the one about causes influencing music preferences) AND INTERVIEWS (interviewed Codesign.io users to detect "pains" in their collaboration processes)
• • PARTICIPATORY DESIGN (led a workshop in Amsterdam with 60+ members on how chatbots could be used in city context, which led to 10+ mockups and prototypes)
• • MACHINE LEARNING (accepted to summer school about Bayesian methods for Deep Learning, led by Google DeepMind and Yandex, in Moscow in August 2017)
• • DATA ANALYSIS (performed an analysis of the public dataset about bike sharing in Bay Area, and introduced methods to balance the usage of bikes to decrease maintenance)

20 Data Analyst Resume Examples & Guide for 2024

Your data analyst resume must clearly showcase your technical expertise. Highlight specific programming languages and analytical tools you are proficient in. Furthermore, demonstrate your experience with data visualization and reporting. Employers want to see your ability to turn complex data into actionable insights.

All resume examples in this guide

Data Analyst Entry Level

Data Analyst Intern

Entry-Level Risk Adjustment Data Analyst

Junior Data Analyst

Senior Data Analyst

Senior Insurance Data Analyst

Data Management Analyst

Data Quality Analyst

Data Reporting Analyst

Excel Data Analyst

Financial Data Analyst

Healthcare Data Analyst

Marketing Data Analyst

SQL Data Analyst

Statistical Data Analyst

Lead Data Analyst

AWS Data Analyst

Data Analytics Manager

Revenue Reporting Data Analyst

Ph.D. in Human-Computer Interaction in love with Electronic Music and Astronomy resume example

Resume Guide

Data Analyst Resume Example

Resume Format

Resume Experience Section

Hard & Soft Skills

Certification & Education on Resume

Resume Summary/Objective

Additional Resume Sections

Key Takeaways

By Experience

Our world today is, more than ever, driven by data and statistics. Every decision businesses make is informed by actionable insights derived from complex data.

Because of this, there’s been a growing recognition of the data analyst role — which explains why this field is becoming increasingly competitive. From 2020 to 2030 only, experts predict that data science fields will grow by 25%, much faster than the average for all occupations.

That’s why a strong data analyst resume is no longer just a luxury but actually a golden ticket to standing out in your job search.

This data analysis resume guide will teach you:

• How to tailor your data analytics resume to specific roles based on the job description
• Tips for creating a resume layout that is both visually appealing and easy to read
• Strategies for highlighting your skills and achievements
• Real-world data analyst resume examples to draw inspiration from

Let’s get to it.

Data Analyst resume example

This data analyst resume shines not just for its content, but for how it efficiently weaves together a narrative of expertise, creativity, and passion. It would be so captivating to recruiters because it:

• Highlights advanced education: which underlines the candidate's deep expertise and specialized knowledge.
• Blends entrepreneurial and academic experiences: showing adaptability and a broad skill set, from leading a company to conducting postdoctoral research.
• Emphasizes relevant skills and projects: such as music recommendation systems and crowdsourcing solutions. Those are strong selling points because they directly align with key data analyst responsibilities.
• Adds a personal touch: by mentioning interests in electronic music and astronomy, making the resume more engaging and memorable.

How to format a Data Analyst resume

The demand for skilled data analysts is ever-growing, but so is the number of candidates vying for these positions. So to stand out from this multitude of applicants , it’s vital to build a well-formatted resume that presents your impact in a digestible manner.

A well-structured resume, tailored to reflect one's career level , not only captures the recruiter's attention but also demonstrates the candidate's professionalism and attention to detail.

Now,there are many ways you can format your resume, and it all comes down to your level of experience. For entry-level applicants, a streamlined layout focusing on education and skills is essential. A seasoned professional, on the other hand, should opt for a more comprehensive format, showcasing a rich history of achievements and experience.

Here are some key formatting tips to consider when building your data analyst resume:

The file format of your data analyst resume has a significant effect on your response rate and job offer rate. PDF is often the safest bet as it preserves your formatting across different devices and platforms. However, some companies use applicant tracking systems (ATS) that prefer Word documents. It’s always a good idea to check the job listing for any specific requirements.

The top sections on a Data Analyst resume:

What recruiters want to see on your resume:.

Looking for inspiration? Explore more captivating resume templates to fast-track your job search journey.

How to write your Data Analyst resume experience

The experience section highlights any past roles in which you've applied your analytical skills and technical knowledge to overcome real-world challenges. This is far from just a list of previous jobs you held but actually a compelling narrative of your professional journey in the world of data analysis.

As we’ve mentioned earlier, expertise is the cornerstone of your resume when applying for highly competitive jobs as a data analyst. The experience section is your opportunity to showcase how you've applied your skills in real-world situations, making it the most critical part of your resume .

So, how do you craft an outstanding resume experience to stand out?

• • Worked with data analysis to support various departments.
• • Responsible for regular data reporting tasks.
• • Assisted in miscellaneous data projects as needed.

Any recruiter would quickly skim over this example and think, 'not interesting,' due to its lack of engaging content. For three simple reasons:

• Duty descriptions are too general and barely mention any specifics about what the job entailed.
• There's no mention of achievements, tools, or methodologies used — which is the first thing headhunters look for.
• The language is passive, failing to highlight any initiative or significant contributions.

Let’s make some changes based on that and see how the section will improve:

• • Analyzed over 1 million data points using SQL to identify trends, contributing to a 15% increase in customer retention.
• • Led a team of 4 in developing automated data reports using Python, reducing report generation time by 40% and enhancing team productivity.
• • Spearheaded a data cleansing initiative, improving data accuracy by 25%, which directly influenced strategic decision-making and increased operational efficiency.

How to quantify impact on your resume

Quantitative metrics are crucial in making a strong impression on recruiters because they provide concrete evidence of your capabilities. Numbers, percentages, and specific metrics transform your experiences from vague statements into compelling proofs of your effectiveness.

Here are the best quantifiable results to show recruters the scope of your impact:

• Increased sales through data analysis: Can you quantify the percentage or amount your data analysis strategies contributed to sales growth?
• Enhanced efficiency in data processing: In what ways did your improvements or innovations reduce the time or resources required for data processing tasks?
• Achieved cost reduction: How much cost savings, in percentage or dollar amount, were realized through your data-driven optimizations?
• Boosted customer satisfaction: Reflect on the increase in customer satisfaction scores or ratings due to your analytical insights.
• Accelerated project completion: Describe the time saved in project completion, such as finishing ahead of schedule, due to your management or analytical skills.
• Influenced decision-making: How did your data insights impact key business decisions, and what changes in market share or business growth were observed?
• Improved data accuracy: Quantify the improvement in data accuracy or reduction in errors achieved through your data validation or cleaning processes.
• Enhanced predictive model accuracy: What was the percentage improvement in the accuracy of predictive models you developed?
• Streamlined reporting processes: Estimate the hours or resources saved per week or month due to more efficient reporting systems or tools you implemented.
• Optimized marketing campaigns: Discuss the improvement in marketing outcomes, like lead generation or conversion rates, due to your data-driven strategies.

How do I write a data analyst resume with no experience

Embarking on a career as a data analyst can be both exciting and daunting, especially when you're just starting out. Your lack of experience may be the reason you’re missing out on some of the positions you’ve always dreamed of.

But it’s vital to remember that every seasoned data analyst was once a beginner, standing exactly where you are now. The key to breaking into this field is crafting a resume that showcases your potential and puts your best foot forward. This is your first step towards landing that dream job in data analysis.

Here are our tips to help you build an appealing resume despite a lack of direct experience:

• Highlight educational achievements: Emphasize relevant coursework , degrees, or certifications in data analysis as a key part of your resume.
• Showcase transferable skills: Many skills you learned from other disciplines like problem-solving and attention to detail can be applicable to data analysis.
• Include relevant projects: Detail any academic or personal projects involving data analysis.
• Demonstrate enthusiasm for learning: Recruiters love to see that you’re committed to growing in the field through courses or self-teaching.
• Leverage internship experience: Use any internships to display workplace adaptability and skills.
• Craft a compelling resume objective: Write a strong objective focusing on your passion and career goals in data analysis.

How to list your hard skills and soft skills on your resume

When hiring data analysts, recruiters seek candidates who possess a dynamic mix of technical skills and interpersonal traits. These abilities are not just perks but necessities, allowing data analysts to excel in their daily tasks and thrive in their roles.

Before we delve into how you can list skills on a resume , let us first define what soft skills and technical skills are.

Soft skills encompass the personal and interpersonal talents that shape how you interact in a professional setting. This includes traits that enable you to navigate complex data challenges, such as problem-solving, articulate data-driven insights to diverse audiences, such as communication, and collaborate across various departments, exemplified by teamwork.

Technical skills refer to the specific expertise required to perform various job functions. In data analysis, this includes proficiency in tools like SQL, Python, R, and Excel for data manipulation, skills in data visualization tools such as Tableau or Power BI, among others.

Blending these soft and technical skills is key to catching a recruiter's eye and distinguishing yourself from other candidates. Here’s how you can do that in your data analyst resume:

Best hard skills for your Data Analyst resume

Best soft skills for your data analyst resume, how to list your certifications and education on your resume.

A strong educational background will significantly impact your job search since it is a key requirement to get hired as a data analyst. In fact, if you’ve been perusing online job offers, you may have noticed that almost all companies expect at least a bachelor's degree in a related field such as computer science, statistics, or mathematics.

The reason for that is straightforward: education demonstrates in-depth foundational knowledge and a commitment to the discipline.

To list education on a data analyst resume, you need to do the following:

• Start with Your highest degree: List your highest degree first, followed by lower degrees.
• Add your degree and major: Specify your degree and major.
• Include the name of the institution: Clearly state the name of the university or college.
• Mention your graduation year: If you're a recent graduate, include your graduation year.

If applicable, you may also mention specific coursework or projects that are particularly relevant to the job to further showcase your expertise and alignment with the role.

Here’s what that should be like on a resume:

Certifications on a data analyst resume are equally important — as they demonstrate ongoing learning and specialization in specific areas of data analysis. They can be particularly crucial for showcasing skills in emerging technologies that may not have been covered in traditional degree programs.

The way you list certificates on your resume is even simpler. As long as it’s relevant and recent, all you have to do is add the name of your certificate to a separate section in your resume.

Below, we’ve gathered a list of the most sought-after data analyst certificates to ignite your job search:

Best certifications for your Data Analyst resume

How to write your data analyst resume summary or objective.

A resume summary is a brief, impactful statement that showcases your qualifications and unique value proposition. It is a crucial element in your data analyst resume because it shapes the first impression recruiters will have about you within a few seconds.

Before we dive into how to craft a powerful resume summary, what's the difference between a resume objective vs. a resume summary?

• A resume summary is most suitable for experienced professionals who have a lot to show on their resumes. It can be a great way to showcase career highlights, feature professional accomplishments, and demonstrate what they can bring to the table.
• A resume objective is typically used by applicants who are entering the workforce, changing careers, or have gaps in their employment history. The objective is more about potential and promises as it focuses on your career goals and how the candidate can benefit the company.

Here are some examples of data analyst resume summaries:

In this first example, the summary is vague and lacks specifics about what the candidate actually did in the job. It uses phrases like "some years of experience" and "familiar with data analysis tools,” which fail to quantify the applicant’s impact within the company.

Additionally, the whole statement feels generic, especially when it mentions "have worked in various industries" without specifying any fields. This lack of detail and quantification fails to differentiate the candidate from others, making the whole resume non-compelling to the hiring manager.

Let’s make some changes and see how it can improve:

This improved summary not only provides a clear picture of the candidate's capabilities but also showcases their potential value to the organization. Here are a few ways it did that:

• Quantifiable expertise: 5 years of experience
• Relevant skills: predictive modeling, business intelligence
• Demonstrates clear impact: increased revenue by 20%

Additional sections for a Data Analyst resume

Additional sections in your resume can play a crucial role in showcasing different aspects of your professional and personal life. They make your application more memorable to recruiters by providing a holistic view of who you are — not just as a data analyst but as a well-rounded individual.

Here are some of the best additional sections to consider for your data analyst resume:

• Strengths: Highlight the key strengths that make you an exceptional data analyst, such as analytical thinking or attention to detail.
• Projects: Showcase specific data analysis projects you've worked on, especially those that had a significant impact or showcase unique skills.
• Awards: List any relevant awards or recognitions you've received to underscore your expertise and dedication in the field.
• Achievements: Mention any notable achievements (either professional or personal) that reflect your determination and growth mindset.
• Passions: Include personal interests or passions that align with the data analysis field. This is an excellent way to demonstrate your genuine enthusiasm for the industry.

Key takeaways

Data analyst resume examples.

Explore additional data analyst resume samples and guides and see what works for your level of experience or role.

Looking to build your own Data Analyst resume?

• Resume Examples

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