Skip to main content
Ace Hired

Resume template

Data analyst resume template

This data analyst resume template is ATS-safe because it uses plain text, conventional headings, quantified bullets, and simple contact details. It is role-specific by foregrounding SQL, Excel, Tableau, Python, dashboards, stakeholder reporting, and measurable business decisions rather than vague analytics statements.

Edit this template

Sample resume

Single-column, plain-text structure with standard headings and quantified bullets.

The person, employers, and figures in this sample are illustrative, written to show the format.

Grace Walker

grace.walker@example.com+44 20 7946 0214linkedin.com/in/gracewalkergithub.com/gracewalker

Summary

Data analyst with 6 years turning operational and commercial data into clear reporting and decisions.

Strong in SQL, Excel, Tableau, Python, dashboard design, and presenting findings to non-technical stakeholders.

Experience

Senior Data Analyst

Brightwave Retail | London, UK | April 2022 - Present

  • Own commercial reporting for a retail group with 340 stores and 2.8M loyalty members.
  • Built Tableau dashboards for sales, margin, and stock that replaced 22 manual spreadsheets and saved 14 hours per week.
  • Analysed promotion performance in SQL, identifying a campaign that cut margin by 4% and recommending its retirement.
  • Automated weekly reporting with Python and scheduled queries, reducing report turnaround from 2 days to 3 hours.
  • Present monthly trading reviews to category, finance, and operations leaders with clear recommendations.

Data Analyst

Meridian Insurance | Leeds, UK | June 2019 - March 2022

  • Analysed claims and policy data in SQL and Excel to support pricing and reserving decisions.
  • Built a renewal propensity report that helped retention teams lift renewals by 7% in one quarter.
  • Created Power BI dashboards for claims ageing used by 45 weekly active stakeholders.
  • Cleaned and reconciled broker data across 12 sources, reducing reporting discrepancies by 33%.

Junior Data Analyst

CityFit | Sheffield, UK | September 2017 - May 2019

  • Produced membership, attendance, and churn reports for 38 gym sites using SQL and Excel.
  • Built a cancellation analysis that identified two onboarding gaps driving 21% of early churn.
  • Standardised KPI definitions across regional managers, reducing conflicting numbers in reviews.
  • Automated a monthly attendance pack with pivot tables and macros, saving 6 hours per cycle.

Skills

Querying

SQL, Excel, Python, VBA

Visualisation

Tableau, Power BI, Looker Studio, Dashboards

Analysis

Cohort analysis, Forecasting, KPI design, Data cleaning, Statistics

Tools

BigQuery, Snowflake, Git, Google Sheets

Education

  • MSc Data Science, University of Edinburgh
  • BSc Mathematics, University of Leeds

Adapting this template for Data analyst applications

For junior applications, keep the template's shape but let tools carry more weight: SQL, Excel, and one visualisation platform proven through concrete reports, the way the CityFit role leans on attendance packs and churn analysis. Mid-level analysts should show the shift from producing reports to changing decisions, as the renewal-propensity work does. Senior candidates need ownership language: this sample's top role owns commercial reporting for a whole retail group and presents monthly to leaders, which is the difference between doing analysis and being accountable for it.

The screening order for analysts is stable: SQL first, then Excel and a visualisation tool, then whether any analysis changed what the business did. That last test matters most and fails most resumes, which is why every role here connects analysis to an action, retiring a margin-cutting campaign, lifting renewals, closing onboarding gaps. Time saved is the other reliably strong currency; replacing 22 manual spreadsheets and cutting report turnaround are outcomes any manager can price.

The common filters: listing tools without a single decision influenced, which reads as report production; vague phrases like data-driven insights that survive in no strong resume; and hiding stakeholder work. Analysts are hired to be understood by non-technical people, so the presenting and standardising bullets in this sample are not filler. Also resist inflating the title; claiming machine learning from one tutorial invites interview questions that end applications.

ATS notes for Data analyst

  • Include literal keywords for SQL, Excel, Tableau, Power BI, Python, dashboards, and reporting.
  • Quantify analysis with hours saved, accuracy improvement, retention, margin, and discrepancy reduction.
  • Separate querying, visualisation, and analysis skills so recruiters can find each cluster cleanly.
  • Show stakeholder decisions, not just charts, to prove business impact and communication scope.
  • Avoid embedded graphs or images because ATS parsers read text and ignore visual content.

Data analyst resume questions

Is Excel still worth listing on a data analyst resume?

Yes. Despite its unglamorous reputation, Excel remains a screening keyword for analyst roles in most industries, and finance and operations teams live in it. List it alongside SQL and Python as this template does, and give it real evidence, like the pivot-and-macro reporting pack here. Omitting it can cost matches with no offsetting benefit.

How do I move from reporting bullets to decision bullets?

Attach a consequence to the analysis. Compare built a Tableau dashboard for promotions with the sample's version, which identifies a campaign cutting margin by 4% and recommends its retirement. Same work, different ending. Go through each bullet and ask what happened next; if the answer involves a person deciding something, write that.

SQL or Python: which matters more for analyst screening?

SQL, without much contest. It appears in nearly every analyst posting and screeners search for it literally, so it should feature in your bullets and not just the skills table. Python earns its place where it did real work, as in this sample's reporting pipeline that cut turnaround from two days to three hours.

Continue your prep

Data analyst interview questions

Practise the data analyst questions recruiters use to test role knowledge, judgement, and depth.

ATS resume checker

Paste this resume into the free checker to see how an applicant tracking system parses your headings, dates, and keywords.