Data Analyst resume keywords
Data analyst screens filter hard on SQL and one BI tool, so those must appear verbatim. But the resumes that convert to interviews go further: they show an analysis that changed something. "Built dashboard" is invisible. "Found the churn driver that recovered $400K in ARR" is not.
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Scoring against Data Analyst keywords.
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Core keywords
These are the terms most consistently used to screen data analyst applications. Include the ones that are genuinely true of your experience, worked into accomplishment bullets rather than dumped into a list — screening reads the whole document, and a human discounts bare keyword lists.
Tools and platforms
Tool names are matched literally. Spell them the way the industry spells them — “PostgreSQL” not “Postgres SQL” — and do not assume a screen infers one from another.
The metrics that carry weight
Keywords get you past the filter. Numbers get you the interview. For data analyst roles, these are the measures hiring managers recognise immediately:
- revenue impact
- hours saved
- conversion lift %
- forecast accuracy
- report adoption
- cost reduction
If you do not have exact figures, estimate honestly and say so. “Roughly 15 hours/week saved” is defensible in an interview and infinitely better than silence. Inventing precise numbers you cannot explain is the one version of this that will actively cost you the job.
Verbs that signal ownership
Open bullets with these rather than with “responsible for” or “worked on”:
Next: the interview
Once the resume clears screening, the questions below are what you will face.
Data Analyst interview questions →