Data Analyst Resume Example

How to write a data analyst resume that proves business impact

The most common mistake on data analyst resumes is listing tools: SQL, Python, Power BI, Tableau. The hiring manager already assumes you know them. What they want to know is which business decision changed because of your analysis. An analyst who builds dashboards nobody opens is worth less than one who answered a question that saved money.

What the data or business lead looks for

• Impact, not deliverables. "Built a dashboard" is a deliverable. "Identified the driver of repeat-purchase decline and the team reallocated campaign spend" is impact. Always write the consequence.
• Real SQL. It is the most tested skill. Complex joins, window functions, CTEs, query optimization. If you are assessed, it will be in SQL.
• Data volume and sources. Where the data came from (ERP, CRM, transactional DB, APIs), how messy it was, what you did to clean it. Cleaning is most of the real work.
• Visualization with purpose. Power BI, Tableau, Looker. What matters is who the dashboard was for and whether they used it. A dashboard with no users is wasted work.
• Communication with non-technical stakeholders. Explaining a finding to a sales director is as valuable as computing it. If you presented to leadership, say so.

Mistakes that get a data analyst resume rejected

• Tool list with no context. "SQL, Python, R, Power BI, Tableau, Excel, Spark" with no projects reads as padding. Fewer tools with cases wins.
• Unadapted coursework projects. The Titanic or Iris dataset impresses no one. If they are your only projects, at least reframe them around a real business question.
• No business outcome. Analysis that led to no decision is an academic exercise. Show what changed.
• Blurring analyst and data scientist. If you have not trained models in production, do not imply it. Different profiles, different pay, quickly detected.
• A portfolio with no explanation. A repo of notebooks without READMEs or conclusions does not get reviewed. Each project needs question, method and finding.

Keywords data analyst ATS filters look for

Use them only where they are true for you: the filter searches for them, but the recruiter verifies them in the interview.

Want to know whether your current resume uses these keywords and whether ATS filters can read it? Analyze it free — three checks a day, no sign-up.

If you are targeting your first data analyst role

Without work experience, your portfolio is your resume — but not any portfolio. You need two or three projects using real data (public datasets or a local business) that answer a concrete business question rather than demonstrate a technique. Each with question, source, cleaning, analysis, finding and recommendation. Master SQL above everything: it is what the technical screen tests. And if in your current job, whatever it is, you built Excel reports that informed decisions, that is data analysis — write it that way.

Frequently asked questions