Data
Data Analyst CV: what gets you shortlisted
Data analyst roles are about turning data into decisions. Screeners look for the questions you answered, the tools you used to answer them and what the business did next. A CV that lists SQL and Tableau without a single decision it influenced is easy to pass over.
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What employers look for in a Data Analyst CV
Screeners check these first. Each one should be visible in your job entries, not only in a skills list.
- Confident SQL, shown through the analysis it enabled.
- A visualisation or BI tool named in the posting, such as Tableau, Power BI or Looker.
- Analyses that led to a decision or change, with the result where you know it.
- Working with stakeholders: turning vague questions into clear analysis and explaining results simply.
- Basic statistics where relevant, such as A/B test analysis or forecasting.
Skills Data Analyst postings often ask for
Listing a skill is not the same as showing it. Resymetry counts a skill as matched only where your CV shows you used it.
- SQL
- Excel
- Tableau
- Power BI
- Looker
- Python or R
- A/B testing
- Data cleaning
- Dashboards
- Stakeholder communication
4 common Data Analyst CV mistakes and how to fix them
Bullets about building dashboards with no mention of who used them.
Fix: Say who relied on the dashboard and what it helped them decide.
No business outcomes.
Fix: Name at least one decision your analysis changed, and its effect if you know it.
Listing Python or statistics you have only studied.
Fix: Keep study-only skills in an education or learning line, not in job achievements.
Jargon that hides the point.
Fix: Write for a hiring manager who is not an analyst: question, method, result.
Weak and strong CV bullets
Illustrative examples, not real candidates. Use your own work and only numbers you can back up.
Weak: Created dashboards in Tableau.
Stronger: Built the weekly sales dashboard in Tableau used by 25 regional managers, replacing a manual Excel report that took a day to prepare.
Weak: Analysed customer data.
Stronger: Found in churn analysis that customers without onboarding calls left at twice the rate, which led the team to make the call standard.
Weak: Ran A/B test analysis.
Stronger: Analysed 14 pricing-page experiments and flagged two early calls that were not statistically significant, avoiding a misleading rollout.
Know your chances for Data Analyst roles
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Data Analyst CV questions
- What skills should a data analyst CV highlight?
- SQL, one BI tool from the posting, spreadsheet skills and clear communication. Show each through an analysis you actually did.
- Do data analysts need Python?
- Many postings list Python or R as a plus rather than a requirement. Include it if you have used it at work, and say what for.
- How do I show impact as a junior data analyst?
- Describe the question, what you found and who used it. A clear decision you informed counts, even without a revenue figure.