Technology CV guide

CV optimisation for Data Analysts

Build a stronger Data Analyst CV by making your evidence of decision-ready analysis from reliable data easy for recruiters and applicant tracking systems to find.

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What a strong Data Analyst CV needs to prove

Show outcomes, not a task list

Connect your actions to a measurable result: time, quality, revenue, cost, safety, service or risk. Add scale so the reader can judge the significance.

Make your evidence easy to verify

Keep employers, titles and dates accurate. Use direct language and include only skills you can support with genuine experience.

ATS keywords for a Data Analyst CV

Use relevant terms naturally where they describe your real work. Mirror the job advert's wording, but do not add a skill you cannot evidence.

SQLPythonPower BITableaudashboardsdata qualitystatisticsstakeholder insight

Common Data Analyst CV mistakes

  1. Leading with tool lists rather than decisions influenced.
  2. Not explaining data scale, quality or validation.
  3. Presenting dashboards as outcomes rather than the action they enabled.
  4. Sending the same generic summary to every employer instead of reflecting the vacancy's genuine priorities.

Worked example: strengthen one bullet

Evidence-led versionBuilt a Power BI retention dashboard from 4.6m customer events, identifying an onboarding drop-off that informed changes and improved 90-day retention by 7%.

Use the structure, not the facts. Replace every detail with evidence from your own experience.

Tailor your CV to the job advert

Paste the advert and your current CV. CVOptimise identifies relevant language, rewrites for clarity and keeps your employers, dates and facts intact.

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