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Data Analyst Resume Example

Analyst resumes tend to describe tools rather than decisions. Knowing SQL is table stakes; what gets you interviewed is evidence that an analysis you ran changed what the business did. Every bullet should end in a decision, a dollar figure, or a behaviour that changed.

Data Analyst resume sample

Daniel Okafor

Senior Data Analyst

Chicago, IL

Summary

Analyst with 5 years turning product and revenue data into decisions. Owns the warehouse models behind forecasting for a 200-person SaaS business.

Experience

Senior Data Analyst · Brightpath SaaS2022 — Present
  • Identified that 62% of churn occurred within 14 days of signup, traced to a failed onboarding email; fix recovered ~$410k ARR.
  • Automated 14 recurring reports in dbt with scheduled Looker delivery, cutting the reporting cycle from 3 days to 40 minutes.
  • Designed and read out 9 checkout A/B tests, including a pricing test that lifted conversion 11%.
Data Analyst · Vantage Retail Group2020 — 2022
  • Built the pipeline dashboard used daily by 40 reps and in weekly forecast reviews, replacing a 6-hour weekly manual process.
  • Rebuilt store-level cohort models in BigQuery, reducing forecast error from 18% to 7%.

Skills

SQL · Python · dbt · Looker · Tableau · BigQuery · Snowflake · A/B testing · Cohort analysis · Excel · Git · Statistics

Education

B.S. Economics & Statistics — University of Illinois, 2020

A composite example. Figures are illustrative — use your own.

What recruiters scan for on a data analyst resume

  • SQL depth first — window functions, CTEs and query optimisation separate analysts from dashboard maintainers
  • The BI tool named in the job description: Tableau, Looker, Power BI. Parsers match these literally
  • Whether you touched the data model or only consumed it — dbt, warehouse design and pipeline work signal seniority
  • Business outcomes attached to analysis, not just the analysis itself
  • Stakeholder language: which teams you supported and at what level, since much of the job is translation

ATS keywords for data analyst roles

Terms that genuinely appear in data analyst job descriptions. Use the ones that are true of you — keyword stuffing is obvious to a human reader and does not help the score.

SQLPythonTableauPower BILookerdbtdata modelingA/B testingETLSnowflakeBigQuerycohort analysisKPI reportingstatistical analysisExcel

Weak vs strong bullets for a data analyst

Created dashboards in Tableau for the sales team.

Built the sales pipeline dashboard now used daily by 40 reps and in weekly forecast reviews, replacing a manual spreadsheet that took an analyst 6 hours a week to maintain.

Shows adoption (40 daily users), where it sits in the business rhythm (forecast reviews), and the cost it removed. A dashboard nobody opens is not an achievement.

Analyzed customer churn using SQL and Python.

Identified that 62% of churn happened within 14 days of signup and traced it to a failed onboarding email; the fix recovered an estimated $410k in annual recurring revenue.

States the finding, the cause, and the money. The tools belong in the skills section — the reason to hire you is that you found something expensive.

Responsible for weekly and monthly reporting.

Automated 14 recurring reports in dbt and scheduled Looker deliveries, cutting the reporting cycle from 3 days to 40 minutes and freeing roughly 25 analyst hours a month for ad-hoc work.

Recurring reporting is often the least interesting part of the job. Framing it as automation you engineered turns routine work into an efficiency result.

Ran A/B tests for the product team.

Designed and read out 9 A/B tests on the checkout funnel, including a pricing-page test that lifted conversion 11%; wrote the sample-size guidance the product team still uses.

Volume plus one specific win plus a durable artifact you left behind — that last part is what distinguishes a senior analyst from an execution-only one.

Common data analyst resume mistakes

Listing tools instead of findings

"Proficient in SQL, Python, Tableau, Excel" tells a hiring manager nothing about judgement. Tools belong in a compact skills block; bullets should carry conclusions and their consequences.

No numbers in a numbers job

An analyst resume without figures is self-defeating. If your findings are confidential, use percentages, orders of magnitude, or relative change instead of absolute revenue.

Hiding the SQL depth

Many analyst JDs screen hard on SQL. If you write window functions, optimise queries, or own models in dbt, say so explicitly — "SQL" alone reads as beginner-level to a technical screener.

Confusing analyst and data scientist framing

Leading with machine learning when the role is business reporting reads as a mismatch, and vice versa. Mirror the vocabulary of the job description you are applying to.

Data Analyst resume FAQ

Should a data analyst resume include a portfolio?

Yes if you are early-career or switching in. One link to two or three well-documented analyses is worth more than a long list of coursework. Lead with the question you asked and what you concluded, not the notebook.

How technical should the bullets be?

Technical enough that an analytics lead believes you, plain enough that a recruiter can match keywords. A practical test: name the technique and the business result in the same sentence.

Do I need Python if the job says SQL and Excel?

No. Mirror the job description. Adding heavy Python and ML language to a reporting role can make you look overqualified or mis-targeted, which costs interviews rather than winning them.

How do I show impact when I only supported other teams?

Attribute the decision, not the outcome you did not own: "analysis that led the growth team to cut paid spend on two channels" is honest, specific and still credits you with the influence.

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