3 Entry Level Data Analyst Resume Examples For 2023

Stephen Greet
Stephen Greet January 12, 2023
3 Entry Level Data Analyst Resume Examples For 2023

You’re looking to break into data analysis and yet, most jobs you see require some analysis experience. What came first, the work experience or the job requiring work experience?

No worries though, there are other ways to showcase that you’d be an excellent entry level data analyst hire for any company smart enough to hire you.

The 3 entry level data analyst resume examples below have worked to help fellow analysts break into the world of data in 2023 so they’re a great place for you to get started on your job search.


Entry Level Data Analyst Resume

or download as PDF

Entry level data analyst resume example

Professional Entry Level Data Analyst Resume

or download as PDF

Professional entry level data analyst resume example


What Matters Most: Your Skills & Work Experience

When you’re looking for your first role in data analysis, any experience counts. Whether it’s an internship or a solo project, put it on your resume! Focus on what you did and the tools you used to do it.

Since you don’t yet have much real-world data analysis experience, your skills section will play a big role in determining whether you get an interview. Recruiters want to see your technical skills here. Vague words like “teamwork” don’t tell much.

9 Popular Entry Level Data Analyst Skills

  • Excel/ Google Sheets
  • SQL (any flavor)
  • Linear regression
  • Python/ R
  • Experimentation
  • A/B testing
  • Data cleanup
  • Tableau
  • Data visualization

When it comes to your technical skills, if you can answer this question, you should include it on your entry level data analyst resume: Would I be comfortable being asked interview questions about that tool/ topic?

Sample Entry Level Data Analyst Work Experience Bullet Points

Now I know what you’re thinking: “Stephen, I’m looking to break into data, I don’t have much relevant experience”. Yes you do!

How did you learn the analysis skills you have? What projects did you work on? Talk about those!

When talking about experience (through internships) or your projects, you want to convince a recruiter your analysis can have impact. So, your bullet points should similarly focus on impact.

We’re math people, so here’s the formula:

[action you took] + [context/skills you used] + [outcome of action]

Here’s a few examples for inspiration:

  • [Built a random forest model] in [scikit-learn] that combined disparate sources into one projection that [outperformed the mean absolute error of the next best projection by 14%]
  • [Built data visualizations] using [SQL and Tableau] for business KPIs that [reduced manual reporting work by 10 hours weekly]
  • [Identified strategic marketing opportunity] for client [through detailed analysis with intern team], making recommendations that [saved client over $10K in yearly campaign costs]
  • [Received, cleaned, and prepped data from client] using [Python, SQL, and Excel] to help data scientists build marketing mix models that [resulted in a lift in ROI of 8 basis points]

If you’re in a time-crunch or are just looking for a quick reference, this section is for you! We’ve helped thousands of entry level data analysts land jobs and here are the most common questions and quick-wins to help you.

Top 5 Tips For Your Entry Level Data Analyst Resume

  1. Any experience can be made relevant
    • That summer you spent serving ice cream? By my estimation you demonstrated reliability, organization, and collaboration. The point is, when you’re looking for an entry level role recruiters don’t expect years of relevant experience.
  2. A little customization goes a long way
    • Since most applicants for entry level data analyst roles don’t have much experience, a great way to differentiate yourself is to customize your resume/ cover letter for each company you apply to. More work, yes, but a higher success rate.
  3. Ditch the summary
    • A career summary is just that, a summary. As an entry level data analyst you likely don’t have an extensive career to summarize. Instead, you may want to add a career objective detailing what you’re looking for in a data analyst role and what you’ll contribute.
  4. Talk about your data analysis projects
    • Employers need some evidence that you can go from idea to analysis in a project. This is the value of your projects section as an entry level data analyst. These can be things you’ve done for class or personally, but you should have something relevant to data!
  5. When it comes to skills, depth over breadth
    • When it comes to your technical skills, it’s much better to demonstrate a strong command of a few skills than have a laundry list of skills on your resume. Nothing is a bigger red flag to recruiters then when they see 5+ programming languages for entry level candidates.

Frequently Asked Questions

  • How long does my entry level data analyst resume need to be?
    • Ideally, you can make your entry level data resume take up one nice, full page. But, it’s better to have a shorter resume than to add a lot of filler content. Remember, recruiters know you’re applying to an entry level role, they don’t expect an extensive working background. The goal of your resume is to convince them you can do the job, not that you necessarily have done the job.
  • I don’t have much experience, what should I talk about?
    • Projects, projects, projects. As an entry level data analyst projects are the best (and sometimes only) way to demonstrate your competency. These projects can be anything. Just ask a question, think of data you can use to answer that question, and do a short write-up of your analysis (any public forum you can link to for this is good).
  • Should I put relevant classes or certifications on my entry level data analyst resume?
    • A bit of a leading question, I admit. But yes, of course include any relevant courses you took in school. For me, including my game theory class led to some interesting conversations in interviews. Similarly, while they’re not as important later in your career, certifications can demonstrate you have the capacity and willingness to learn data analysis.