Check your data analyst CV against the job advert
Data analyst adverts want tools and impact: what you queried, what you built, and what decision it helped. Show both halves.
Start with your advert
Every data analyst advert is different. The list below is what adverts for this job usually ask for, not what yours does. So start with your advert:
- Read the advert and copy out every "must have" or "essential" line, then the "desirable" ones.
- For each one, find the line in your CV that proves it. If you can't point to a line, that's a gap.
- Fill the gap with something true: a duty, a setting, a qualification or a result you really have. If you don't have it, say what you have that's closest, or leave it out.
Our guide to matching your CV to a job description goes through this in more detail.
What data analyst adverts usually ask for
SQL
Why they askSQL is the most common must-have for analyst roles.
How to show itSay what data you queried and why.
Example lines: fill the gaps with your own facts- Wrote SQL queries in [database or warehouse] to [analyse what], for [team].
BI and dashboards
Why they askAdverts often name Power BI, Tableau or Looker.
How to show itDescribe a dashboard: who used it and what for.
Example lines: fill the gaps with your own facts- Built [Power BI / Tableau / Looker] dashboards for [audience] to track [metrics].
Excel and Python or R
Why they askExcel is near-universal; Python or R appear in more technical roles.
How to show itName the libraries or functions you actually use.
Example lines: fill the gaps with your own facts- Used Python ([pandas / other libraries]) to [clean, combine or analyse what].
Turning analysis into decisions
Why they askEmployers value analysts who explain findings to non-specialists.
How to show itGive an example of an insight and what happened next.
Example lines: fill the gaps with your own facts- Found [insight] in [data], which led [team] to [decision or change].
Data quality
Why they askClean, trusted data is part of the job.
How to show itDescribe checks or fixes you made.
Example lines: fill the gaps with your own facts- Set up [checks / documentation] that [improved data quality how].
Only use a line if it's true for you. Swap each [gap] for your own detail: the setting, the number, the tool or the result. If you can't fill a gap honestly, cut that part of the line.
Mistakes that cost data analyst applications
- Tool lists with no examples of analysis.
- Claiming advanced statistics you couldn't explain at interview.
- No sense of the business question behind the work.
Questions
How do I show data skills without an analyst job title?
Use any work where you analysed data: reporting in admin or finance, retail sales analysis, or a portfolio project with a public dataset.