Data analyst resume example
This is the document our Data Analyst · Dashboard template renders — impact tiles up top, evidence underneath — and it scores 95/100 against our 30 published ATS rules. The persona finds money and says so in dollars, which is precisely what analytics hiring managers scan a page for.
Measured by exporting this exact resume and running it through the 30 rules we publish. Certified: we only badge templates at 90 or above, a stricter bar than the 85 our checker calls interview-ready, so the design leaves headroom for your own content.
Opens in the editor with this content in place — replace it line by line. No signup, no watermark on the PDF. The sample PDF is the exact export the score was measured on.
The live document, not a screenshot. Names and employers are fictional.
Why these bullets work
Every line below is taken verbatim from the resume above.
“Own revenue and funnel analytics for a $140 million brand; build and maintain the 12 dashboards the growth team plans against”
Scope and the artefacts the team depends on. It places the analyst in the planning loop, not the reporting queue.
“Found a 9% drop in second-order conversion among first-time buyers through cohort analysis; the fix recovered $1.8 million a year”
A specific finding, the method, and the money it recovered. This is the bullet an analytics lead hires for.
“Designed and read out 60 A/B tests with the onboarding and pricing squads, each with a written decision”
Sixty readouts with a decision each. It shows a habit of closing the loop rather than producing charts.
“Built the LTV and payback model that reset paid-media budgets by channel; blended payback improved from 11 to 8 months”
A model that moved budgets and improved payback. Analysis that changed a decision is worth more than analysis that described one.
Making it yours
- Attach dollars to at least two bullets — revenue lifted, spend recovered, cost avoided. If the exact figure is out of reach, a defensible estimate with its basis ('~$90k/yr at current volume') still beats none.
- Match the tool line to the shop you're applying to: Power BI vs Tableau vs Looker, dbt, GA4, Python. Analytics screeners filter on the exact BI product before they read a single bullet.
- Name who consumes your work and how often — this resume's dashboards are opened weekly by the leadership team. Adoption is the difference between analysis and decoration.
- Keep one bullet that shows a checked trade-off, like the flat-repeat-rate cohort line here — it is the fastest way to read as an analyst rather than a report-runner.
Common questions
Do I need Python, or is SQL enough for a data analyst resume?
SQL does the heavy lifting in this example and in most analyst jobs. Python (pandas) appears once and honestly — list it if you can survive an interview question on it, skip it if you can't. One trusted tool beats five decorative ones.
Should I link a portfolio or sample dashboards?
Link one thing that opens instantly and needs no login — a public dashboard or a short write-up of a single analysis. This resume's header link does that job; a GitHub full of coursework does not.
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