For Data Analysts
A data analyst resume that proves impact, not tool familiarity.
Every analyst resume lists SQL. The ones that get interviews show a question, a method, and a number that moved. DraftlyCV rewrites your bullets into that shape and keeps the file parser-safe for analytics hiring pipelines.
- • Headline and summary tuned to the exact analyst title you are targeting.
- • AI rewrites that convert dashboard work into business outcomes.
- • Tool stack grouped the way screeners read it: SQL, BI, Python/R, Excel, cloud.
- • Project slots with links for portfolio work and case studies.
- • Free ATS check against any analytics job description.
The bullet formula that works for analytics roles
Question → method → outcome. Start with the decision the business needed, name the technique and tool, close with the measurable result.
Prefer percentages and absolute numbers over adjectives. 'Automated a weekly report, saving 6 analyst-hours per week' beats 'improved reporting efficiency'.
Show ownership of the data path where you had it — ingestion, modelling, definition of metrics — not just the final chart.
Keep two projects with links even after your first job. They are the fastest way for a hiring manager to verify depth.
Frequently asked questions
A headline with your analysis stack, a two-line summary, quantified impact bullets, a tools section (SQL, Python/R, Excel, Power BI or Tableau), and two portfolio projects with links.
Name the question, the method, and the business outcome. 'Built a churn cohort model in SQL and Power BI that cut monthly churn 1.8 points' is stronger than 'created dashboards'.
For entry-level, yes — two clean projects with a dataset, a notebook or dashboard link, and a written finding will beat a longer skills list.
Mirror the job posting's order. Most analyst roles screen for SQL first, then a BI tool, then Python or Excel depth.