Data Analyst Resume: Beat the AI Screener
Data analyst roles bridge business and technical skills. ATS systems look for SQL proficiency, visualization tools, and clear business impact from your analysis work.
Common ATS Mistakes for This Role
- 1Saying "analyzed data" without specifying what data, what tools, and what outcome
- 2Missing SQL as a top-line skill — it's the #1 searched keyword for analyst roles
- 3Not mentioning BI tools by name: Tableau, Power BI, Looker, Metabase
- 4Omitting statistical methods: regression, hypothesis testing, cohort analysis
- 5Writing technical jargon without business context — always connect analysis to decisions made
Top Keywords AI Screeners Look For
SQLPythonTableauExceldata visualizationstatistical analysisA/B testingETLreportingKPIscohort analysisbusiness intelligence
Before & After: Bullet Rewrites
1
Created reports for the marketing team
Built automated weekly reporting dashboard in Tableau tracking 8 KPIs across 5 marketing channels, reducing manual reporting time by 12 hours/week
2
Analyzed customer data to find trends
Performed cohort analysis on 500K+ customer records using SQL and Python, identifying retention drop-off that led to product changes increasing 90-day retention by 18%
3
Helped with A/B testing
Designed and analyzed 15+ A/B tests using statistical significance testing (p<0.05), directly informing pricing strategy that increased average order value by 22%
Pro Tip
For analyst roles, always include the SIZE of data you worked with (rows, users, revenue). "Analyzed 2M+ transaction records" scores significantly higher than "analyzed transaction data."
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