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Data analyst resume: skills, keywords & examples

Last updated May 31, 2026

Data analyst resumes win when they connect analysis to a decision or dollar. Anyone can run a query; the candidates who get hired show what the business did differently because of their work.

What hiring teams look for

  • Tools fluency - SQL above all, plus a viz tool and often Python/R.
  • Business impact - analyses that changed a decision, metric, or process.
  • Clear communication - turning data into something stakeholders act on.

Key skills and keywords

Match the posting, but the core set is: SQL, Excel, a BI tool (Tableau, Power BI, Looker), Python/R, data visualization, A/B testing, ETL, and domain metrics (retention, funnel, LTV). List tools you can defend in a technical screen.

Example bullet points

Strong
Built a churn dashboard in Looker that flagged at-risk accounts 30 days earlier, helping CS retain $410k of ARR in two quarters.
Strong
Ran an A/B test on the checkout funnel (SQL + Python) that identified a 9% drop-off; the fix lifted conversion 6%.

Common mistakes

  • Listing tools with no evidence of using them on a real problem.
  • Reporting activity ("built 20 dashboards") instead of impact.
  • Burying the business outcome at the end of the bullet - lead with it.
Put this into practice
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