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Data Analyst · United Kingdom format

The Data Analyst résumé format for United Kingdom.

Your data analyst experience doesn't change across borders — but how you present it does. Here's what a data analyst résumé for United Kingdom should include and leave off: the personal-data norms, length, date format, and language recruiters there expect — plus the data analyst keywords the ATS scans for. Resuvia reforms your résumé to these conventions in one click, without fabricating anything.

Personal details on a United Kingdom résumé

  • PhotoLeave off
  • Date of birthLeave off
  • NationalityOptional
  • Marital statusLeave off
  • GenderLeave off

What else matters in United Kingdom

  • State work authorisation only if it affects eligibility.

Data Analyst keywords to lead with

Whatever the market, a data analyst résumé is scored on role-relevant terms. Mirror the ones the job description uses — but only those genuinely in your experience.

SQLPythonpandasNumPyTableauPower BILookerdbtBigQuerySnowflakeA/B testingexperimentationcohort analysis

Data Analyst résumé mistakes to fix first

  • 01

    Listing tools without context. "SQL, Python, Tableau" in a skills section is fine; the bullets need to show you used them.

  • 02

    No statistical reasoning surfaced. Mentioning A/B tests without the design (sample size, metric, result) reads as box-checking.

  • 03

    Treating "data analyst" and "data scientist" as one role. Tailor — JDs that lean ML want Python/stats; pure BI roles want Tableau/SQL/storytelling.

Best-effort guidance on common United Kingdom conventions, not legal advice — verify specifics before relying on them, especially anti-discrimination rules.

FAQ

Do you put a photo on a Data Analyst résumé in United Kingdom?
Photo: leave off. Leave it off — United Kingdom anti-discrimination norms apply regardless of role.
How long should a Data Analyst résumé be in United Kingdom?
2 pages (CV). Keep the strongest data analyst bullets near the top.
What date format should I use for United Kingdom?
DD/MM/YYYY. Use it consistently across every role and education entry.
Which Data Analyst keywords matter for the ATS?
Lead with role-relevant terms such as SQL, Python, pandas, NumPy, Tableau, Power BI, Looker, dbt — but only ones genuinely in your experience. The optimizer flags which the target JD wants that you're missing.