Data Analyst Resume Example That Passes ATS Screening

Data Science & Analytics · Entry Level · Updated 2025-03-20

Breaking into data analytics is tough when every 'entry-level' posting asks for 2 years of experience. The good news: if you know how to frame your academic projects, internships, and self-directed work the right way, you can build a resume that competes. This example shows how an early-career data analyst leads with skills (the stuff hiring managers actually search for) while still telling a compelling story about what they've done with those skills.

ATS Keywords for Data Analyst Resumes

ATS systems scanning Data Analyst applications look for these terms. The resume above weaves them in naturally rather than listing them outright.

Section-by-Section Writing Tips

Professional Summary

At the entry level, name the tools you know and the types of problems you've solved. Mention the teams or stakeholders you've supported. Skip the 'recent graduate seeking opportunities' line. Show that you already think like an analyst, not a student.

Experience Section

Even short internships deserve 3-5 detailed bullets. Quantify the data you worked with (rows, sources, categories). Name the tools in context. If your work influenced a decision, say so. 'Built a dashboard' is okay. 'Built a dashboard that replaced a manual process and was used by the marketing team weekly' is much better.

Skills Section

For entry-level analysts, this section does heavy lifting. Organize by what you do (query, visualize, program, manage data) rather than by tool type. Include proficiency context where helpful (e.g., 'SQL (PostgreSQL, BigQuery)' tells more than just 'SQL').

Education Section

Include GPA if it's above 3.4. Mention your capstone or thesis if it's analytically relevant. Relevant coursework is worth listing if you don't have much work experience yet, but drop it once you have a year of professional work.

Full Resume Sample

Why This Resume Works

Skills-first layout matches how recruiters actually search for entry-level analysts. For entry-level data roles, recruiters often filter by tools first: 'Do they know SQL? Tableau? Python?' Putting skills at the top, organized by function, means the resume passes that initial screen before the reader even gets to experience. This is especially effective when you have fewer years of work history.

The internship reads like a full-time role because of specificity. Marcus doesn't hedge with phrases like 'assisted with' or 'helped the team.' He states exactly what he built, how big the data was, and what happened as a result. A 10-week internship can carry as much weight as a year of experience if you write about it with this level of detail.

Academic work is framed as professional output, not homework. The research assistant role doesn't mention grades or class assignments. It talks about published visualizations, policy briefs, and stakeholders (county officials). Reframing academic work in terms of deliverables and audience turns it into legitimate professional experience.

Common Data Analyst Resume Mistakes

Hiring managers reviewing Data Analyst resumes flag these problems repeatedly. Each one can knock your ATS score or land your application in the rejection pile.

• Listing 'Microsoft Office' as a skill when you should be specifying Excel capabilities (pivot tables, Power Query, advanced formulas)
• Describing internship work passively ('was responsible for helping with data tasks') instead of owning specific deliverables
• Omitting the size or complexity of datasets you worked with, making it impossible to gauge your experience level
• Padding the skills section with tools you've only watched tutorials on but never used on a real project
• Not including a capstone project, personal project, or Kaggle competition when you have limited professional experience
• Leaving off soft skills context like presenting to stakeholders or collaborating across teams, which differentiates analysts from spreadsheet operators

More Resume Examples

Related ATS Guides