Data Analyst Resume Template

Data analyst resume template for Word and Google Docs. Tools sit high, and a Selected Analyses section lists each question, method and decision.

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What is in the file

[Your Name]

[Data Analyst] · [Domain, e.g. marketing, product, operations or finance analytics] · [SQL and your BI tool]

[City, State] · [email@example.com] · [(555) 555-0100] · [LinkedIn or portfolio URL]

Summary

[Data analyst with N years answering (domain) questions in (SQL dialect, BI tool, Python or R). Best example: (one analysis and the decision it led to). Looking for (the kind of team and data in the posting).]

Skills

Query and scripting: [SQL (name the warehouse: BigQuery, Snowflake, Redshift), Python with pandas, or R]
Reporting: [Tableau, Power BI or Looker; Excel with pivot tables and Power Query]
Methods: [A/B test readouts, cohort and funnel analysis, regression, forecasting, data modeling in dbt]

Experience

[Data Analyst], [Company], [Team you support, e.g. Growth]

[City, State or Remote] · [Mon YYYY] – [Present]

[Answered (business question) for (team or leader) using (data source and method); result: (decision taken, e.g. campaign paused, price test changed)]
[Built (dashboard or report) used by (N people, how often), replacing (manual report or spreadsheet) and saving (hours per week)]
[Analyzed (N experiments) for (product or marketing), including (sample size, guardrails), and recommended (ship, stop, rerun)]
[Improved data reliability: (tests, metric definitions, a cleaned table) that cut (errors, reconciliation time, conflicting numbers)]

[Previous job title], [Company]

[City, State] · [Mon YYYY] – [Mon YYYY]

[Produced (recurring report) for (audience), covering (metrics, number of stores, regions or products)]
[Automated (manual step) with (SQL, Python, Power Query), cutting (time) from (before) to (after)]
[One line on growth: trained (users) on self-serve reporting, or took over (a data source or domain)]

Selected Analyses

[Title of analysis] · [Link to notebook, dashboard or write-up] · [Question, data used, and the finding in one sentence]

[Title] · [Link] · [Why it matters for this posting's domain]

Education

[B.S. or B.A. in (statistics, economics, mathematics, business or your field)], [University], [YYYY]

[Certificate, e.g. a SQL or analytics program], [Provider], [YYYY]

An analytics hiring manager reading a resume is checking two things in order: can you get the data yourself, and did anyone act on what you found? This template answers the first with a tools block directly under the summary, SQL on the opening line, and the second with experience bullets that start from a business question and end with what changed.

Between Experience and Education sits a Selected Analyses section. It holds two or three pieces of work a reviewer can read: a public notebook, a dashboard on open data, a write-up of an internal study described without confidential figures. Early-career analysts and people moving into analytics from finance, operations or research lean on it most; experienced analysts can cut it to one line or remove it.

Fill each bracket with your own facts, and where a number is confidential, give its direction and what was decided. A completed page in this layout is the data analyst resume example.

Updated 2026-10-13.

How to fill in each section

Summary: domain, tools, one decision
Analysts are hired into a domain as much as a function, so name yours in the first sentence: marketing, product, supply chain, finance, healthcare. Then name the query language and reporting tool you actually use daily. The second sentence earns the interview: one analysis and the decision it changed, in plain words a hiring manager outside analytics would follow. Avoid describing yourself as data-driven or detail-oriented; the decision sentence shows both.
Skills: SQL first, then the BI tool in the ad
Put SQL on the first line and name the warehouse you query, because Snowflake, BigQuery and SQL Server experience are listed separately in many postings. The reporting line should carry the BI tool from the job ad if you have used it, then Excel. Keep methods to the ones you could explain at a whiteboard: cohort analysis, test readouts, regression. A dozen languages here suggests breadth without depth; three or four tools you use weekly reads stronger.
Experience: question, method, decision
Open each bullet with the question someone needed answered, not the query you ran. Then say briefly how you answered it and what happened next: a budget moved, a feature shipped or was dropped, a process changed. Dashboards count only with their audience: how many people opened them and what they replaced. Data quality work is easy to undersell; tests that stopped a wrong number reaching finance are a real result. Name the team you supported in the heading so the domain is clear.
Selected Analyses: work a reviewer can read
This block matters most when your job titles do not say analyst yet. Pick public data close to the employer's world, such as a retailer's sales, a city's transit or a hospital's wait times, and write up the question, the method and what you would recommend. A clean notebook with a short conclusion beats a long one with every cell left in. Internal studies can appear here too, described by question and outcome with the numbers removed.
Education: degree plus one relevant certificate
Give your degree, school and year. Quantitative fields such as statistics or economics need no explanation; for other degrees, the experience and analyses above carry the case. A single certificate line helps career changers and new graduates when it matches the tools in the posting. Leave off courses already shown by a project above, and remove the certificate line once you have two or three years in an analyst role.

See it filled in

The data analyst resume example uses this structure with a realistic candidate, with versions for entry, mid and senior level.

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Questions about the data analyst resume template

Should I put Selected Analyses above Experience?

Move it up when your current job is outside analytics, such as retail, teaching or customer service, and the analyses are the strongest proof you can do the work. Keep it below Experience once your job history already shows analysis with results.

How do I describe an analysis when the numbers are confidential?

Use relative terms and the outcome: the share of cancellations fell after the change, the team ended a campaign that was not paying back, finance closed the month two days earlier. A hiring manager wants evidence that your work was used, not your former employer's revenue.

Do I need Python for a data analyst resume?

Not for every role. SQL and a BI tool cover many postings, especially on reporting-heavy teams. List Python or R only if you have used it for real work, such as cleaning files, automating a report or running a statistical test, and show that use in one bullet.

How is this different from the data scientist template?

This layout centers on questions, reporting and decisions. If your work is mostly building and deploying predictive models, the data scientist resume template gives experiments and models more room.

Is it free?

Yes. The Word files and the Google Docs copy are free to download, edit and use for any application. There is no signup and no email.

Will it read correctly in an applicant tracking system?

The layout is one column with standard headings and real text: no tables, text boxes, icons, columns or images, which are the parts parsers most often misread. Keep it that way as you edit.

Word or Google Docs?

Use whichever you edit in. The Word file opens in Microsoft Word, Pages and LibreOffice. The Google Docs link asks you to make a copy in your own Drive; the original stays blank for the next person. Send the posting the format it asks for, usually .docx or PDF.

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