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Data Analyst resume example

Analysis is worth a bullet when a decision came out of it — every one here does.

Invented for this page. The name, the employers and every number in it are made up — a real resume is somebody’s personal data and is not ours to publish.

Tomás Herrera

tomas@example.com | +44 20 7946 0912 | Manchester, UK

Summary

Analyst working on retention and pricing for subscription businesses. Five years turning messy operational data into decisions somebody actually took.

Experience

Senior Data Analyst

Jan 2022 – Present

Halden Retail Group, Manchester, UK

Built the churn model that redirected £1.2m of annual retention spend away from customers who were never going to leave.

Cut the weekly trading report from 6 hours of manual work to 20 minutes by rebuilding it in dbt and Looker.

Ran the pricing test across 340 stores that raised margin 2.4 points with no measurable volume loss.

Data Analyst

Sep 2019 – Dec 2021

Brightline Insurance, Leeds, UK

Found the claims-routing error costing £180k a year that four teams had each assumed was somebody else's.

Rebuilt 23 legacy reports onto one warehouse model, retiring three conflicting definitions of “active customer”.

Education

BSc, Mathematics and Statistics

Sep 2015 – Jun 2018

University of Sheffield, Sheffield, UK, 2:1

Skills

Analysis: SQL, Python, dbt, Experiment design, Forecasting

Reporting: Looker, Power BI, Snowflake

Projects

uk-retail-footfall

Feb 2023 – Aug 2023

Author | https://github.com/example/uk-retail-footfall

Open dataset and notebook series on high-street footfall, cited in two local-government planning reports.

Why it is written this way

  • Each analysis names what changed as a result

    “Built a churn model” is a task. “Built the churn model that redirected £1.2m of retention spend” is a result, and it is the same project.

  • The tools are listed once, not repeated per role

    Repeating SQL under every job is the keyword-stuffing pattern the match engine penalises, and a human reader discounts it the same way.

  • A project section carries the work an employer did not pay for

    Public, checkable, and often the most specific evidence on a mid-career analyst's resume.

Shapes to fill in

Each blank is yours to complete. These are the same scaffolds the builder offers for this occupation — none of them says anything until you fill it in, which is what keeps them useful rather than a lie somebody else wrote.

Made something faster or cheaper

  • Cut ___ from ___ to ___ by ___
  • Reduced ___ by ___% by ___
  • Removed ___ from ___, saving ___ per ___
  • Automated ___, taking it from ___ of manual work to ___

Shipped something

  • Shipped ___, used by ___
  • Built ___ that ___, replacing ___
  • Launched ___ in ___, ___ ahead of ___
  • Delivered ___ across ___ with ___

Improved quality or reliability

  • Cut ___ defects from ___ to ___ by ___
  • Raised ___ from ___ to ___ over ___
  • Eliminated ___, ending ___ that had cost ___
  • Introduced ___, cutting ___ incidents by ___%

Also called

Analytics Consultant · Applied Scientist · Data Analyst · Data Analytic Scientist · Data Analytics Scientist · Data Analytics Specialist · Data Architect · Data Consultant · Data Economist · Data Engineer

From the O*NET occupation database. Worth checking which of these a posting uses, because that is the wording its keyword search will be built on.

What a parser reads from this resume

This is the actual plain-text output for the document above — the same text an applicant tracking system extracts, and the same text this app hands you when you download the .txt. Nothing is lost between the page and the parser, which is the whole argument for a single column of real text.

Tomás Herrera
tomas@example.com | +44 20 7946 0912 | Manchester, UK

SUMMARY

Analyst working on retention and pricing for subscription businesses. Five years turning messy operational data into decisions somebody actually took.

EXPERIENCE

Senior Data Analyst | Jan 2022 - Present
Halden Retail Group, Manchester, UK
- Built the churn model that redirected £1.2m of annual retention spend away from customers who were never going to leave.
- Cut the weekly trading report from 6 hours of manual work to 20 minutes by rebuilding it in dbt and Looker.
- Ran the pricing test across 340 stores that raised margin 2.4 points with no measurable volume loss.

Data Analyst | Sep 2019 - Dec 2021
Brightline Insurance, Leeds, UK
- Found the claims-routing error costing £180k a year that four teams had each assumed was somebody else's.
- Rebuilt 23 legacy reports onto one warehouse model, retiring three conflicting definitions of “active customer”.

EDUCATION

BSc, Mathematics and Statistics | Sep 2015 - Jun 2018
University of Sheffield, Sheffield, UK, 2:1

SKILLS

Analysis: SQL, Python, dbt, Experiment design, Forecasting
Reporting: Looker, Power BI, Snowflake

PROJECTS

uk-retail-footfall | Feb 2023 - Aug 2023
Author | https://github.com/example/uk-retail-footfall
- Open dataset and notebook series on high-street footfall, cited in two local-government planning reports.
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