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Data Analyst · India format

The Data Analyst résumé format for India.

Your data analyst experience doesn't change across borders — but how you present it does. Here's what a data analyst résumé for India 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 India résumé

  • PhotoOptional
  • Date of birthOptional
  • NationalityOptional
  • Marital statusOptional
  • GenderOptional

What else matters in India

  • Photo and personal details are common; not required.

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 India 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 India?
Photo: optional. It's optional for India; the role doesn't change that.
How long should a Data Analyst résumé be in India?
1–2 pages. Keep the strongest data analyst bullets near the top.
What date format should I use for India?
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.