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Data analyst resume: proof over tool lists

Anyone can list SQL. The analyst who gets shortlisted shows the question they answered and the decision it changed.

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Job titles this covers

Atlas
  • Data Analyst
  • Business Analyst
  • Product Analyst
  • Insights Analyst

Clean two-column header with a single-column body — enough structure to separate projects from experience without breaking parsing.

  • Starts from the recommended template
  • Section order matches this role
  • Export as Letter or A4

What this document has to prove

Analyst resumes converge on the same tool list, which makes the tool list useless as a differentiator. What separates candidates is whether the analytics changed something: a decision, a cost, a process, a forecast anyone acted on.

This guide is about making that evidence visible in a format a parser can read and a hiring manager can skim.

What a recruiter searches for

These are the terms a hiring team filters on. Include the ones that are true of your work — our checker tells you which are missing, it never inserts them for you.

SQL
Write it, and show it in a bullet: the model you built, not just the language.
BI tools
Tableau, Power BI, Looker, Metabase — name the one you actually own dashboards in.
Programming
Python, R, dbt. Include pandas, numpy, tidyverse or dbt models where true.
Statistical vocabulary
Regression, cohort analysis, forecasting, A/B testing, segmentation, significance.
Data engineering touchpoints
Data warehouse (Snowflake, BigQuery, Redshift), ETL/ELT, data quality, documentation.
Business outcome words
Retention, churn, conversion, margin, utilisation, cost per acquisition.

How to write it, section by section

The structure that works

Analyst resumes benefit from a summary that names the specialism and the domain — "product analyst, subscription SaaS, activation and retention" beats "data-driven professional". Then experience, then a tight skills block.

  • Summary: specialism, domain, and one proof point with a number.
  • Experience: each role gets a one-line scope statement, then three or four outcome bullets.
  • Projects: a portfolio project with a link is powerful when you are breaking in.
  • Skills: SQL, BI tool, language, warehouse, statistics — one line each, no ratings.
  • Education: include relevant modules or a dissertation only for early-career.

The four-part analyst bullet

Question, data, method, consequence. If any part is missing, the bullet reads like a job description.

  • Question: "Why did week-one retention drop for self-serve signups?"
  • Data: "18 months of event data across 200k accounts."
  • Method: "Cohort analysis in SQL, validated against billing records."
  • Consequence: "Found onboarding step three was the drop-off point; the fix became the next quarter's roadmap item."

Keywords without pretending

A recruiter searches the tool plus the domain. If the advert says "Looker" and you have used Looker, write Looker — not "BI tooling". If you have used Metabase, write Metabase and let your bullets carry the transferable skill; do not relabel your experience as something it was not.

The honest middle ground is a bullet that names the transfer: "Built the same cohort model in Metabase; moved to Looker when the team consolidated BI."

Breaking in with no analyst title

Plenty of analysts start from operations, finance, marketing or teaching. Rebuild the resume around analysis you have actually done — the spreadsheet model, the dashboard, the forecast — and describe it in analytics vocabulary. Add one portfolio project with real data and a written conclusion, and link it.

Do not claim years of experience you do not have. Claim the work you did, described accurately.

Portfolio and links

A GitHub or notebook link is only worth including if it is readable. A notebook with a clear question, clean code and a written conclusion outperforms twelve unfinished experiments. Put the link in the header, and make sure the repository has a README that explains the business question.

Mistakes that end the first read

Each of these is common in this role specifically, and each one costs a real application.

  • A skills section that lists every tool ever touched, with no evidence for any of them.
  • Bullets that describe dashboards built but never a decision changed.
  • Confusing duties with outcomes: "responsible for reporting" is not a result.
  • Claiming "advanced Excel" as the headline skill for a senior role.
  • Linking to a portfolio that is private or half-finished.
  • Ignoring the domain: analytics resumes for e-commerce and for healthcare should not read the same.

Questions people ask

Does a data analyst resume need a portfolio?
For your first analyst role, yes — one finished project with a clear question and conclusion is worth more than a certificate list. After two or three years of real work, the job history carries the weight.
Should I list every tool I know?
No. List the ones you would be comfortable being tested on and that appear in the advert. A long list invites questions you may not want.
How do I show impact when my team owned the outcome, not me?
Describe your part precisely. "Part of the team that rebuilt the retention model; I owned the SQL layer and the validation against billing" is honest and still substantial.
Is a maths or economics degree required?
No, but the advert may ask for a numerate degree. If yours is in another field, put the analytical work — modules, projects, the job you did — where a reader can see it.

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