CV template
Data analyst CV template
A data analyst CV fails in one of two ways: a list of tools with no evidence of judgment, or a wall of business prose with no searchable skills. The fix is structural. Keep SQL, Python and your BI stack scannable in a sidebar, and spend every experience bullet on a decision your analysis changed.
Data analyst CV — Professional template
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Professional's tinted sidebar keeps your toolset (SQL, Python, Tableau, dbt) permanently visible while the main column carries your analysis work. Recruiters filter analysts by tools first, so giving them their own column pays off.
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The one rule: analysis is only worth its decision
Hiring managers do not hire analysts to write queries; they hire them to change decisions. "Built a churn dashboard in Tableau" describes labor. "Built a churn dashboard that flagged at-risk accounts two weeks earlier, and the retention team's outreach cut churn 12%" describes value. Every bullet should try to complete the chain: analysis, decision, outcome.
If the outcome was not measured, name the decision instead: which pricing option was chosen, which campaign was killed, what the executive team stopped debating. An analyst who frames work this way immediately reads as senior, whatever the years say.
Where the tools go, and how to name them
Recruiters and ATS searches filter analysts hard by tools: SQL first, then Python or R, then the BI layer (Tableau, Power BI, Looker), then the modern data stack (dbt, Snowflake, BigQuery) for more technical roles. Give these a dedicated skills list, phrased exactly as job ads phrase them. Write "Power BI", not "Microsoft business intelligence tooling".
Keep Excel on the list; it is still searched for constantly, and "advanced Excel (INDEX MATCH, Power Query, pivot models)" tells a hiring manager more than a bare "Excel". Statistics belongs here too if you can defend it: A/B testing, regression, cohort analysis.
Structuring experience when your work is projects
Analyst work is naturally project-shaped, so structure bullets as mini case studies: the question, the method in one clause, the outcome. "Answered why trial conversion dropped 9%: cohort analysis in SQL traced it to a signup-flow change, which was rolled back and conversion recovered in two weeks." One sentence, complete story.
Aim for three to five bullets per role, at least half with numbers. Vary the metric: revenue, cost, time saved, accuracy improved, decisions accelerated. Ten bullets that all end in "increased revenue" read as fiction.
Breaking in: the junior analyst CV
Without professional experience, your projects section is your experience. Two or three self-directed analyses of real public datasets, each with a linked notebook or dashboard and a genuine finding, beat any certificate list. Phrase them exactly like job bullets: question, method, finding. Then let your education and certificates (Google Data Analytics, relevant coursework) support rather than lead.
Steal this wording
Example data analyst summary
Data analyst with 5 years of experience turning product and marketing data into decisions for B2C subscription businesses. At Luminara, built the experimentation reporting that reallocated 30% of paid spend and raised trial-to-paid conversion 2.1 points. Fluent in SQL, Python and Tableau; happiest when a stakeholder leaves with an answer, not a chart.
Example achievement bullets
- Built self-serve revenue dashboards in Tableau used weekly by 60+ stakeholders, retiring 20 hours per month of ad-hoc reporting
- Traced a 9% drop in trial conversion to a signup-flow change through SQL cohort analysis; the rollback recovered conversion within two weeks
- Designed and analyzed 25+ A/B tests across pricing and onboarding, lifting trial-to-paid conversion from 11.2% to 13.3%
- Migrated reporting logic into dbt with tested models, cutting metric discrepancies between teams to near zero
- Automated the weekly executive report with Python, reducing preparation from 6 hours to 20 minutes
Adapt the numbers and systems to your own work — never copy a claim that isn't true of you. The structure is the part worth stealing.
Keywords that get searched
Skills to include on a data analyst CV
Hard skills
Soft skills — shown, not listed
List hard skills verbatim; prove soft skills inside your bullets instead of naming them.
Questions, answered
Which tools should a data analyst CV lead with?
Do data analytics certificates help?
Should I include a link to my portfolio or notebooks?
Data analyst vs data scientist: which title do I use?
How do I quantify analysis work that didn't directly make money?
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