ATS Resume Template

Data Analyst Resume Template

Analyst resumes fail for a specific reason: they describe tools instead of decisions. Listing SQL, Tableau and Python tells a hiring manager what you touched, not what changed because you touched it. The template below is written the other way round, and the score on this page is the actual output of the proof engine, not a marketing number.

100/100Proof Engine Score
100%Evidence Density
264Word Count
Scores computed from the actual resume below by the same engine the studio runs.
What recruiters screen for

Why most data analysts don't get the call

The decision, not the dashboard

"Built 40 dashboards" is a workload. "Built the pricing model behind $2.4M of margin decisions" is an outcome. Analysts get filtered out at the first skim because their bullets end at the artefact. Push every bullet one step further: who acted on it, and what moved.

Row counts and refresh cadence are your scale numbers

Engineers have latency and QPS. Analysts have rows modelled, tables owned, reports served, and how fast the data lands. "180M order rows" and "a 6am freshness SLA" tell a reviewer what size of environment you can survive in.

SQL depth gets probed within ten minutes

Window functions, CTEs, incremental models and query cost show up in nearly every analyst screen. If you have tuned a warehouse bill or rewritten a nightly job, that belongs on the page — it separates you from someone who only ever wrote SELECT statements in a BI tool.

Say which methods, not "statistical analysis"

Keyword filters match literal terms. A/B testing, cohort analysis, regression, forecasting and attribution are searchable. "Strong analytical skills" matches nothing and signals nothing.

The example resume

A scored data analyst resume

Every bullet below was graded by the proof engine. The score and evidence density above are its actual output — computed at build time, not written by hand.

Marcus Delaney

Senior Data Analyst

marcus.delaney@hey.com+1 (312) 555-0176Chicago, ILlinkedin.com/in/marcusdelaneygithub.com/mdelaney
Summary

Analyst with five years turning warehouse data into revenue decisions at marketplace and fintech companies. Modelled 180M rows in SQL and dbt, cut reporting turnaround 70%, and drove pricing changes worth $2.4M.

Experience
Meridian Marketplace2022Present
Senior Data AnalystChicago, IL
  • Own the pricing analytics model end-to-end, informing $2.4M in annual margin decisions with 4 stakeholder teams each quarter.
  • Design dbt models over 180M order rows against a 6am freshness SLA, cutting the finance close from 9 days to 2.
  • Automate 23 recurring Looker reports, returning 31 hours per week to a 6-person analytics team.
  • Lead the weekly experiment review, raising the share of A/B tests reaching significance from 34% to 71%.
Kestrel Financial20202022
Data AnalystChicago, IL
  • Built a churn model in Python flagging 12K at-risk accounts per month, driving a retention campaign worth $780K.
  • Replaced 40 hand-maintained spreadsheets with a governed Snowflake layer, removing 6 recurring reconciliation errors.
  • Partnered with marketing to attribute 14 acquisition channels, reallocating $1.1M of spend and lifting ROAS 27%.
Bramble Retail Group20192020
Business AnalystAnn Arbor, MI
  • Developed 60 Tableau dashboards used weekly by 240 staff across 3 business units.
  • Reduced warehouse query cost 44% by refactoring 18 nightly jobs, scaling to 3x data volume with no added spend.
  • Delivered a demand forecast at 8% MAPE, cutting stockouts 22% across 90 SKUs.
Education
University of Michigan20152019
B.S. StatisticsAnn Arbor, MI

Minor in Economics

Skills
Query & Languages:SQL, Python, R, DAX
Analytics & BI:dbt, Looker, Tableau, Power BI, Mode
Data Platforms:Snowflake, BigQuery, Airflow, Fivetran
Methods:A/B testing, cohort analysis, regression, forecasting, attribution
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Loads into the editor pre-filled. Swap in your own content and watch the score move.

ATS keywords

What the keyword filter is looking for

Applicant tracking systems match on literal strings. Spell each term the way the job posting spells it and group related skills so people and parsers can recover the context.

Query & languages
SQLPythonRDAXpandasNumPy
BI & modelling
dbtTableauLookerPower BIModedata modellingstar schemasemantic layer
Platforms
SnowflakeBigQueryRedshiftDatabricksAirflowFivetranETLdata warehouse
Methods
A/B testingexperimentationcohort analysisregressionforecastingattributionsegmentationKPI reporting
Notes on the template

Why each choice was made

Why the skills section is split four ways

A single block of twenty tools reads as noise and trips the engine's ungrouped-skills rule. Four labelled groups let a keyword filter match the string and a human skim the shape of your stack in about two seconds.

Why dollar figures appear next to technical work

Analyst work is easy to describe as internal plumbing. Attaching the business number — $780K retention campaign, $1.1M reallocated spend — is what moves a bullet from support function to revenue function in a reviewer's head.

Where to put a portfolio

One link in the header, next to LinkedIn. A GitHub with three real notebooks beats a Projects section that repeats what your job already proves.

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