Resume example · ATS-friendly

Data Analyst Resume Example

A data analyst resume should prove three things: you can pull the data, you can ask the right question of it, and you can change a decision because of it. Use this example to phrase your work in those terms, and to pass the ATS keyword scan on the way.

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Sample data analyst resume

The same resume in the Modern, Executive and Elegant templates. Switch between them to see how the layout changes, then copy the structure into your own.

Minimal and left aligned, with thin rules and a near black accent.

Alex Morgan

Data Analyst, Product Analytics & Experimentation

alex.morgan@example.com
(555) 555-0100
Austin, TX
linkedin.com/in/alex-morgan-example

Summary

Data analyst with 4 years partnering with product and growth teams. I translate fuzzy product questions into testable hypotheses, ship the dashboards and experiments to answer them, and brief stakeholders on what the result actually means for next quarter's roadmap. Heavy on SQL + Python; comfortable owning the data model in dbt.

Skills

SQL (Postgres, BigQuery, Snowflake)
Python (pandas, NumPy, scikit-learn)
R
dbt
Looker / Tableau / Power BI / Metabase
ETL / ELT pipelines
A/B testing & statistical inference
Cohort & funnel analysis
Forecasting (ARIMA, Prophet)
Git, Jupyter, dashboards (Streamlit)

Experience

Data Analyst

Northwind Labs, 2022 to Present

Designed and ran 14 A/B tests on the signup funnel; the top 3 winners lifted week-1 retention by a combined 9.4 points.
Built the company's first cohort-retention dashboard in Looker, replacing four conflicting hand-rolled spreadsheets; now the single source of truth for the weekly growth review.

Associate Data Analyst

Brightline Group, 2019 to 2022

Owned the dbt model for billing events; cut nightly run time from 47 minutes to 11 by rewriting two CTE-heavy queries as incremental models with proper unique keys.
Forecasted churn six weeks out with 87% MAPE accuracy using Prophet + a logistic-regression overlay on usage signals.

Education

Bachelor of Science

Riverton University, 2015 to 2019

Sample content. Alex Morgan, the employers and the school shown above are fictional, and the contact details are reserved placeholders.

How to write a data analyst resume

Lead with impact bullets, then add a Tools section. 'SQL' alone is not enough: list the dialects (Postgres, BigQuery, Snowflake) so the ATS keyword scan hits the actual job listing's stack.

Show one A/B test or one dashboard you can talk about for ten minutes in an interview. Specifics beat breadth.

Avoid 'data-driven' as a self-description. The whole role is data-driven; it conveys nothing.

Why data analyst applications get screened out

These are the failures specific to this role: the ones a generic CV guide will not warn you about.

'SQL' listed with no dialect, when the posting screens for Postgres, BigQuery or Snowflake specifically.
Dashboards listed by count with no indication of who used them or what changed.
Tool list dominated by Excel and Tableau with no evidence of query-level work.
Analysis described without the decision it informed: the part that distinguishes an analyst from a reporter.
No statistical vocabulary at all in a posting that clearly expects experimentation.

What drives pay for this role

Analyst pay separates mainly on how close the work sits to decisions. Reporting and dashboard maintenance sits below analysis that changes what a business does, which sits below roles with modelling or experimentation ownership. The other levers: SQL depth versus tool-only fluency, industry (finance and tech generally above non-profit and public sector), and whether the title is analyst, senior analyst or analytics engineer, a distinction that carries real weight in some organisations and none in others, so read the responsibilities rather than the label.

Data Analyst resume questions

How much SQL should I show?: Enough to be unambiguous about level. Name the dialects, and mention the harder things if you have done them: window functions, CTEs, query optimisation on large tables. 'SQL' alone reads as beginner whether or not you are one.
Do I need Python or R?: Depends on the posting. Many analyst roles are SQL and BI only. If the posting asks for Python, name the libraries you actually use (pandas, numpy, scikit-learn), rather than the language alone.
How do I show impact when I only produce analysis?: Attach the decision. 'Analysis of churn cohorts that informed the pricing change shipped in Q3' shows the work reached a conclusion someone acted on. That is the whole distinction between analysis and reporting.
Should I include a portfolio?: One or two pieces of real analysis, written up, are worth more than a gallery of chart screenshots. If the underlying data is confidential, reproduce the approach on a public dataset instead.

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