Data analyst resume examples from 2025

How To Write A Data Analyst Resume

Data analysts work with data management programs and other software to provide companies with the essential information that guides business decisions. Being an adept data analyst requires attention to detail, creativity, and adaptability.

Of course, the best way to increase your chances of being hired is to improve your resume. As a prospective data analyst, the skills, qualifications, and work history outlined on your resume can give you the edge you need to stand out.

Luckily, we’ll discuss what makes a data analyst’s resume successful, as well as provide professional tips and examples.

Key Takeaways:

• Include a project you worked on or find some way to quantify your achievements in your Resume Summary Statement.

• You should include six to 12 listed hard skills on your data analyst resume, the most important of which include Data Analysis, Data Quality, and Business Intelligence.

• Use keywords like SQL, Analysis, and Innovation to make your resume ATS-friendly. This will give you a better chance of competing with other Data Analysts.

What Should Be Included in a Data Analyst Resume

As you may already be aware, a successful resume has several different parts that provide the hiring manager with essential information. So, to better understand these components and how to nail them, here they are outlined:

1. Header and Contact Information

   While it might seem basic, it is nevertheless important to include your contact information in the correct formatting. This will serve as your header, so the hiring manager knows who you are, where you’re from, and how to contact you as soon as they open your resume. If you’re not sure what information to include, consider:

   • Your Name. should be the biggest text on the page (preferably bolded or capitalized) and be at or near the top of the document.

   • Your Address. While you don’t need to list your actual address, be sure to include your city and state so the employer understands your general location.

   • Your Email Address. Include a professional email (preferably with your first and last name as the address), but also ensure you’re not using a work or school-provided email.

   • Your Phone Number. Including your phone number can be essential for phone interviews or if the hiring manager simply wants to call you when providing information.

   Example:

   JAMES MOORE
   Boston, MA 02108| 333-111-2222 | james.moore@email.com

2. Resume Summary Statement or Objective Statement

   Just below your header, you should include a resume summary statement or objective statement. This simple intro is only one to three sentences but plays a crucial role in summarizing who you are and what you have to offer. Think of it as the equivalent of a hook in a storybook.

   Though, a summary statement and an objective statement are slightly different. A summary statement is more skills-orientated, while an objective statement focuses on your career goals.

   For example:

   • Summary Statement: Adaptable data analyst with over four years of experience using many different database types to accomplish big data capture. Successfully used data set to increase company ad revenue by 17%, with the communication skills, data interpretation, and business intelligence needed to guide important decisions.

   • Objective Statement: Data analyst seeking an opportunity to draw upon my skills in data analysis, procedures, Python, and data management to help increase the effectiveness of company products and marketing, ultimately with the goal of reducing costs and increasing revenue.

   Regardless of which formatting you choose, it’s important to find a way to highlight your accomplishments as a data analyst.

3. Hard and Soft Skills

   The next step in crafting the perfect resume is to state all of your most important skills. But, knowing the difference between hard and soft skills is important. Here are some tips to keep in mind when writing your resume's skills section:

   • Include 6 to 12 skills in bullet point form

   • List mostly hard skills related to Data Analysis, Data Quality, and Business Intelligence

   • Emphasize the skills that are most important for the job (use the job description as a guide)

   Listing more hard skills is especially important for data analysts, where experience with relevant technologies and the positive results that experience provides are essential. However, listing a few soft skills can also be valuable, as they're highly transferable and can make you more appealing as a candidate.

   Overall, think about what skills you have that would be crucial to your performance as a data analyst. For example, the most common skills written on a data analyst resume include:

   • Data Analysis (14.9% of resumes). An overarching skill that can cover anything from programming languages to procedures. While you should go into more detail than this in your skills section, including “data analysis” does have the benefit of appealing to ATS Software.

   • Procedures (7.7%). These are established ways to perform a certain task. For example, a data analyst might follow a specific procedure that serves as a roadmap for how to gather and process information.

   • Python (6.9%). As one of the most common object-oriented and all-purpose coding languages, Python is a crucial skill for any data analyst.

   • Data Management (5.4%). Good data management requires a process that collects and stores data as safely and cost-effectively as possible. Efficient data management helps a company use the data to make better business decisions.

   • R (4.1%). This programing language is great for statistical computing, and its popularity with data analysts stems from the fact that it was built for data analysis by data scientists.

   • Data Quality (4.1%). Data quality is another overarching skill that covers things like data collection and business process skills.

   • Data Collection (3.6%). Data analysts use programming languages and other tools to collect information. The most important goal of data collection is to gather the information that is rich and accurate for statistical analysis.

   Additionally, other hard skills you could add include:

   • Logic and analysis

   • Business process

   • Relational databases (MySQL)

   • SAS

   • Pattern and trend identification

   • Data mining and data QA

   • Database design

   • SharePoint and advanced Microsoft Excel functions

   • Tableau and Qlik

   • Business intelligence (BI)

   • Risk management

   • System Administration

   • Quantitative methods

   • Data warehousing

   • Tech support

   • Survey creation

   The top soft skills for data analysts include:

   • Communication & collaboration. Collaboration and Communication Skills are ATS keywords for data analysts for a reason. These skills are highly useful when you’re presenting information to other employees or when you’re trying to gather information from consumers.

     Good collaboration and communication also allow you to work on company projects more effectively.

   • Innovation. Another ATS keyword, innovation, shows that you can learn and master new technologies. It will also inform the hiring manager that you have the mind for turning data into useful information.

   • Attention to detail. Data can be dense and monotonous, which is why it’s so important for data analysts to pay attention to the details. A detail-orientated data analyst is far more likely to pick up on important correlations.

   With other useful soft skills including:

   • Adaptability

   • Critical thinking

   • Risk assessment

   • Organization

   • Creativity

   • Decision-making

   • Time management

4. Experience and Work History

   Arguably the most important part of your resume, showcasing your work experience, allows you to prove the skillset you claim to have. Recruiters and hiring managers expect to see your experience listed in reverse chronological order, meaning your most recent experience should be listed first.

   Remember that as much as you might want to include that job from almost a decade ago, you should only focus on your most recent and relevant work. The hiring manager doesn’t need to read a 20-year-long history of every job you’ve ever had.

   Additionally, craft your job descriptions to impress. Instead of vague informational blurbs, make sure most of your bullet points discuss impressive achievements from your past positions. Whenever you can, use numbers to contextualize your accomplishments for the hiring manager reading your resume.

   Here are some examples of useful work history descriptions on a data analyst resume:

   Project Coordinator, Full-Time, 03/2017 to Current
   Granite Telecommunications

   • Helped Manage 115 multi-site rollout projects for Americold Logistics VoIP phone conversion.

   • Used Visio to map out cube configurations.

   • Maintained accurate retail inventory levels through EOW to ensure that AB product was always in stock.

   • Championed reorganization efforts for department knowledge base articles to assist with IT support procedures.

   Data Analyst, Full-Time, 05/2018 to Current
   Accenture Federal Services

   • Worked with SMEs to elicit and document the Business Rules and requirements for business processes.

   • Designed dashboards based on requirements that reduced operating costs by 14%.

   • Created SSIS packages to import data from different data sources.

   • Executed and implemented complete SDLC for enterprise Systems (ERP applications).

   Market Research Analyst, Full-Time, 09/2016 to Current
   Johnson & Associates

   • Created new scripts that increased website performance by 22%.

   • Identified and analyzed new potential products, services, markets, and advertising opportunities.

   • Interpreted customer behavior through surveys and other forms of data analysis, ultimately using that information to increase positive customer service feedback by 30%.

   • Implemented tools that analyze marketing results, trends, and investment levels.

   Operations Internship, Part-Time, 09/2019 to 04/2021
   HP

   • Assisted in the early testing of the Procurement Compliance SharePoint.

   • Devised and implemented communications processes and knowledge transfer between the India team and our US-based team.

   • Trained ten to 15 new testers and repair technicians per month on proper procedures.

   • Employed RDP or KVM for remote troubleshooting purposes.

   • Aided in troubleshooting/recovery tasks such as server hang issues, failed drives, connection issues, and failed scripts.

5. Education

   In addition to your experience, listing your educational background is an important addition to any data analyst resume. In fact, 92% of those currently working in the field have a degree, the most common of which is a Bachelor’s Degree (65%).

   Similarly to your experience section, be sure to list your most recent and important accomplishments at the top of the section. Then, you should include:

   • The name of your school

   • The date you graduated (month, year, or just the year are both appropriate)

   • The name of your degree

   • If you graduated more than 15 years ago, you should consider dropping your graduation date to avoid age discrimination.

   With optional subsections including:

   • Academic awards (Dean's List, Latin honors, etc. )

   • GPA (if you're a recent graduate and your GPA was 3.5+)

   • Extra certifications

   • Academic projects (thesis, dissertation, etc.)

   Example:

   Bachelor's Degree In Business 2014 - 2018
   California State University - San Bernardino San Bernardino, CA

6. Certifications

   Certifications aren’t a requirement for your resume, but they can certainly give you an edge. Employers want to see that data analysts can get results, so if you have any of these certifications, make sure to put them on your data analyst resume:

   • Certified Management Accountant (CMA)

   • Chartered Financial Analyst (CFA)

   • Project Management Professional (PMP)

   • Associate - Data Science Version 2.0

   • Certified Coding Specialist (CCS)

   • Certified Business Intelligence Professional (CBIP)

   • Certified Data Management Professional - Data Management (CDP-DM)

   • Oracle Certified Associate - Oracle9i Database Administrator (OCA)

Five Key Resume Tips for Writing a Data Analyst Resume

Having the correct formatting and eye-catching sections is crucial for any resume, but these five key tips will also help you stand out in one of the most in-demand tech fields. Consider the following:

1. Mention Your Projects

   While the details of your experience and education do a lot to inform the recruiter or hiring manager, the specific projects you’ve accomplished as a data analyst might be exactly what they’re looking for. Your projects will show not only how you put your skills to use but also the benefits your work can achieve.

   For example, if a company wants to hire a data analyst so they can better understand and tailor to their customers, mentioning that data management and survey project you did that yielded advice on improving customer experience would be valuable.

   This is especially true if you can tie a positive number or figure to the completion of your project (e.g., the number of customers visiting the website increased by 15%).

2. Outline the Right Skills

   The work of a data analyst is varied, as companies will have different goals achieved through different programming languages. That means reading the job description of any data analyst position thoroughly is very important.

   After researching the job, you can pick and choose which of your skills you want to highlight on your resume. For instance, if the job mainly requires you to use Python and discover insights about upcoming products, you’ll want to put skills relating to those two things front and center.

   Just remember that you don’t want any more than 12 skills listed (for readability’s sake). So, even if you have dozens of related skills to add to your data analyst resume, do your best to narrow them down to the most relevant.

3. Quantify As Much As Possible

   Your accomplishments as a data analyst make you desirable, and even more so when you quantify them. For example, Instead of writing that you “helped a company increase advertising revenue,” it’s better to say that you “increased advertising revenue by 17%”.

   Accurate numbers, dates, and percentages will improve the quality of your resume. However, even if you only have a rough idea of the numbers, it’s still good to give an estimate.

4. Make Your Resume ATS-Friendly

   Data analyst jobs are in demand right now, and that leads to a lot of applicants. In turn, this increases your chances of being judged by ATS Software.

   An applicant tracking system (ATS) is a piece of software employers use to collect, scan, organize, and rank applications. The key to getting your resume past ATS and into the hands of hiring managers is smart keyword usage.

   Some common keywords positively ranked for data analyst resumes include:

   • SQL

   • Statistics

   • Data Analytics

   • Database

   • Analysis

   • Communication Skills

   • Technical

   • Business Intelligence

   • Collaboration

   • Innovation

5. Increase Readability With Formatting

   The way you choose to write and structure your resume can make or break your readability. This is especially true when the skills and job descriptions you write as a data analyst are so detailed.

   That’s why we recommend following the steps outlined in this article, as well as these other tips:

   • Avoid first-person pronouns

   • Use bullet notes for skills and job descriptions (Always favor bullet notes over writing paragraphs)

   • Use acceptable font types and sizes

   • Use past tense when describing previous jobs and present tense for current jobs

   • Bold important details that you want to highlight (e.g., quantities, skills, etc.)