ATS keywords for a data analyst resume
Many employers keep applications in an Applicant Tracking System (ATS), where recruiters search and sort them by the skills the role needs. Use these terms where they honestly describe your experience, so your resume is easy to find and easy to read:
Key skills to highlight
- ▸Querying and transforming data with SQL
- ▸Building dashboards and reports
- ▸Turning analysis into clear recommendations
- ▸Data modelling and quality checks
- ▸Communicating insight to non-technical stakeholders
Credentials Australian employers screen for
- ▸Degree in a quantitative or related field (or strong demonstrated skills)
- ▸BI or cloud certifications where held
- ▸Named tool proficiency (SQL, Power BI, Tableau, Python)
- ▸A portfolio of dashboards or analyses where possible
Common mistakes to avoid
- ▸Listing tools without the insight or decision they enabled.
- ▸No impact, analysis that changed nothing reads as busywork.
- ▸Using generic terms instead of the exact tools in the job ad.
- ▸No evidence (portfolio or quantified outcomes) to back the claims.
Data Analyst CV example: before and after
One experience entry, written twice. The numbers are illustrative, the structure is what matters.
Before
Data Analyst, 2022 to present. Analyse business data and produce reports for stakeholders. Build dashboards, run queries, and support the team with ad hoc requests. Maintain reporting and ensure data is accurate.
It names no tools, so an ATS matching on SQL, Power BI or Python finds nothing, and because no analysis is linked to a decision, the whole entry reads as reporting upkeep rather than work that changed anything.
After
Data Analyst | Microsoft Certified: Power BI Data Analyst Associate (PL-300), credential ID XXXXXX | SQL, Power BI, Python, advanced Excel
National retail group, 320 stores, customer and trading analytics team | January 2022 to present | Full time
- ▸Built and maintained 14 Power BI dashboards used by around 180 store and category managers, replacing a weekly Excel pack and removing roughly 6 hours of manual reporting per week.
- ▸Wrote SQL against a data warehouse of 400 million plus transaction rows for cohort, basket and margin analysis, with data modelling into star schemas to keep report refresh under 4 minutes.
- ▸Churn and lapsed-customer analysis in Python that segmented the loyalty base and informed a win-back campaign, lifting reactivation 12 per cent against a matched control group.
- ▸Statistical analysis of a 26-store price trial, quantifying uplift and confidence intervals so the category team could scale the change to the full network with a known revenue effect.
- ▸Built ETL and data quality checks that flagged duplicate and missing store submissions before publication, cutting reporting corrections from about 5 per month to fewer than 1.
Same data, same dashboards. The rewrite names the exact tools an ATS matches on, then ties every analysis to the decision it drove and the number that moved, so the work reads as commercial impact rather than a tool list.
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Frequently asked questions
Which tools should a data analyst list?
Name the exact tools the job ad calls for first, commonly SQL, Power BI or Tableau, advanced Excel, and Python or R. ATS matches on the specific names.
How do I show impact as a data analyst?
Tie analysis to outcomes: 'Built a churn dashboard that informed a retention campaign reducing churn 12%'. The decision your work drove is what matters.
Do I need a portfolio?
It helps. A few sample dashboards or analyses, even anonymised, give employers proof beyond a skills list.
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