Data analyst resume example with decisions, not dashboards
A dashboard is an artefact; the decision it changed is the achievement. Analyst resumes that lead with tools sound interchangeable, so lead with the decision and keep the tooling one line below.
A summary that carries a number
Product analyst supporting a subscription business: SQL against a 40-million-row event warehouse, cohort retention models in Python, and weekly readouts to the growth team. Retired two dashboards nobody opened and replaced them with one churn view.
Replace every figure with your own. If you never tracked the metric, use the scale you can defend — team size, volume per shift, contract size, or how long the situation lasted.
Keywords a data analyst search looks for
- SQL
- Python
- pandas
- dashboard
- A/B testing
- cohort analysis
- retention analysis
- Looker
- Tableau
- data modelling
Use the ones that are true of your work, spelled the way the posting spells them. Skills belong in a plain list with one item per entry — icon rows and rating bars frequently extract as a single unreadable string.
Five bullets to adapt
- Built the churn cohort view that the retention team now reviews weekly, replacing four ad-hoc spreadsheets.
- Ran the pricing experiment readout, including power analysis and a segment breakdown that changed the rollout plan.
- Rewrote a recurring report from 40 minutes of manual SQL to a scheduled query, freeing a day per month.
- Documented the event schema and naming convention adopted by three product teams.
- Trained six non-analysts on the self-serve dashboard, reducing routine requests to the team.
Skills section
SQL (window functions, CTEs) · Python (pandas) · dbt · Looker · Tableau · A/B testing · Cohort analysis · Data modelling · Excel · Stakeholder communication
Lead with the decision
Format each bullet as decision, method, result: "The team changed the rollout after the segment breakdown showed the effect was concentrated in one plan." A reader learns both that you can analyse and that people act on it.
State data volume and query depth
"SQL" alone is ambiguous. "Window functions and CTEs against a 40-million-row events warehouse" tells the reader the shape of the work. If your depth is joins and aggregations, say that instead of implying more.
One artefact is enough
Link one dashboard or write-up if it is public and still maintained. A portfolio of five abandoned notebooks signals the opposite of what you intend.
Questions about this page
- Do I need a portfolio to get a data analyst job?
- It helps most when your work history is not analytical. One or two projects with a clear question, a stated method, and a conclusion are enough; the conclusion matters more than the visual polish.
- How technical should the SQL on my resume be?
- Name the constructs you can write unaided: joins, aggregations, window functions, CTEs, query tuning. Interviews test exactly this, so the resume should predict what you can do live.
- Should I list business-domain knowledge?
- Yes, one line. Analysts are hired into a domain — subscription billing, logistics, clinical operations — and domain familiarity shortens ramp-up more than another library.