May 2026 · 7 min read
A data analyst CV needs to demonstrate technical skills, business impact, and analytical thinking simultaneously. Here's how to do all three.
Personal statement → Technical skills section → Work experience (achievements not duties) → Projects (if relevant) → Education → Certifications. For data analysts, the technical skills section should come before work experience — it's the first thing recruiters check and the primary ATS filter.
Advertisement
Data analyst work experience should lead with business impact, not technical process. "Built a dashboard in Tableau" is weak. "Built a real-time sales performance dashboard used by 45 account managers daily, reducing reporting time from 4 hours to 20 minutes weekly" is strong. Every bullet should answer: what did you build/analyse, what was the business context, and what was the measurable result?
For junior and mid-level data analysts, a portfolio of 2–3 completed analysis projects on GitHub or Kaggle adds significant credibility, particularly if your work experience is limited. Senior analysts with strong track records and quantified achievements in their CV don't need a portfolio — the CV evidence speaks for itself.
If you include a portfolio link, make sure it's well-maintained, the code is clean and documented, and the projects are completed (not just started). A messy GitHub with half-finished notebooks is worse than no portfolio at all.
Advertisement
CVCraft AI writes a complete, ATS-optimised UK CV for any role or experience level.
Write my CV free →