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Data analyst resume example

A data analyst’s resume with six years of experience, written for product, marketing and e-commerce analytics roles. At this level, hiring managers look past tools to judgment: which questions you chose, how you tested them and what the business did next.

Data analyst resume example, page 1 of 1Brennan OyelaranData Analyst, E-commercebrennan.oyelaran@example.com · (404) 555-0129 · Atlanta, GA · linkedin.com/in/brennanoyelaranSummaryData analyst with six years in retail and banking, the last three running analytics for an online home goodsbusiness with $140 million in annual sales. I design experiments, define the metrics teams are judged on, andturn findings into changes merchants and marketers can act on the same week.ExperienceData Analyst IIJan 2023 – PresentPeachtree Home Goods · Atlanta, GA•Analyze 45 A/B tests a year on site and email; a checkout test I designed and read out lifted conversion 3.4%($2.6 million a year).•Built the dbt models and Looker explores behind the weekly trading report, replacing 9 spreadsheets used by40 people.•Found that free-shipping thresholds drove 22% of returns on low-price items; the change I proposed saved$480,000 in year one.•Defined the company’s customer lifetime value metric with finance, now used to set paid marketing budgets.•Mentor two junior analysts and review their SQL before results go to leadership.Data AnalystMar 2021 – Dec 2022Marigold Credit Union · Atlanta, GA•Built a member attrition report in Tableau that the branch network used to target 3,000 at-risk members aquarter.•Segmented 180,000 members by product use, shaping a credit card campaign that beat its sign-up goal by30%.•Moved 25 monthly reports from SAS to SQL and Python, cutting run time from a day to under an hour.Operations AnalystJul 2020 – Feb 2021Southbend Retail Group · Atlanta, GA•Tracked store labor and sales for 60 locations and flagged weekly outliers to district managers.EducationB.S. in Economics2016 – 2020Georgia State University · Atlanta, GASkillsSQL (BigQuery, Snowflake) · Python (pandas, statsmodels) · dbt · Looker · Tableau · A/B testing ·Experiment design · Google Analytics 4 · Excel · Cohort and funnel analysis · Forecasting · Metric definition ·Stakeholder management
Data analystUse this example

What recruiters look for

  • Decisions you influenced: a price, a budget, a product change. Name it and put a number on the result.
  • Experimentation: test design, sample sizes, reading results honestly. Most mid-level product and marketing analyst roles ask about it.
  • Metric ownership: definitions you wrote, metrics leadership uses, disputes you settled.
  • Modern tooling: a cloud warehouse, dbt or another modeling layer, a BI tool, Python. It shows you can work without a data engineer holding your hand.
  • Raising the level of the team: reviewing others’ queries, mentoring, documentation.

Writing the summary

Your years, the domain you know (e-commerce, banking, healthcare, SaaS), the scale of the business, and the type of analysis you are best at. End with how fast your work turns into action, if that is true.

The summary in this example

Data analyst with six years in retail and banking, the last three running analytics for an online home goods business with $140 million in annual sales. I design experiments, define the metrics teams are judged on, and turn findings into changes merchants and marketers can act on the same week.

Marketing analyst

Marketing analyst with five years measuring paid search, social and email for consumer brands spending $20 million a year on media. I build attribution and incrementality tests that tell marketers where the next dollar should go, and dashboards they check without asking me first.

Analyst aiming for a data scientist role

Data analyst with five years in subscription software who now builds churn and forecasting models in Python alongside my reporting work. Completed a part-time M.S. in Analytics in 2026 and looking for a data scientist role focused on experimentation and causal questions.

Bullet points that work

Strong lines for this role, beyond the ones in the example. Borrow the shape and put in your own numbers.

  • Designed a holdout test that showed retargeting ads had no incremental effect, freeing $900,000 a year in media budget.
  • Cut the time to answer a standard question from 3 days to 1 hour by building a self-serve Looker explore for merchandising.
  • Forecast weekly demand for 1,200 products within 8% error, used by buyers to place orders.
  • Reconciled web analytics with order data and found 11% of revenue missing from attribution reports; fixed the tagging with engineering.
  • Ran the analysis behind a loyalty program redesign that raised repeat purchase rate from 28% to 34%.
  • Wrote the team’s experiment checklist (power, guardrail metrics, stopping rules), adopted for 60 tests a year.
  • Built a funnel report that exposed a 40% drop-off on mobile address entry, fixed in the next release.
  • Presented quarterly customer insights to the executive team and 3 board meetings.
  • Replaced 15 manual Excel reports with scheduled SQL and dbt models, saving about 25 analyst hours a month.
  • Trained 30 merchandisers to use self-serve dashboards, cutting ad hoc requests to the team by a third.

Skills to list

Hard skills

  • Advanced SQL (window functions, CTEs, query tuning)
  • A cloud warehouse (BigQuery, Snowflake, Redshift)
  • dbt or another modeling layer
  • Looker, Tableau or Power BI
  • Python or R (pandas, statsmodels, tidyverse)
  • A/B testing and statistical inference
  • Cohort, funnel and retention analysis
  • Forecasting basics
  • Web and product analytics (GA4, Amplitude, Mixpanel)

Soft skills

  • Framing the question before the query
  • Storytelling with data
  • Pushing back on a bad metric
  • Mentoring junior analysts
  • Working with finance and product

Certifications and licenses worth listing

  • No certification is expected at mid-level; results and tools in your bullets carry the decision.
  • dbt Analytics Engineering Certification: a plus if you are moving toward analytics engineering.
  • Google Analytics Certification or Tableau Certified Data Analyst: useful for marketing-heavy roles or employers that name the tool.

Length and format

One page up to about seven years. Give the current role four or five bullets with business results, the previous one three, and anything older a single line. Education sits at the bottom with no coursework.

Common mistakes

  • Leading with tools (“Used SQL and Tableau to create reports”). Lead with the decision or the result, then mention the tool.
  • Quoting test results without the business effect. “Lift of 3.4%” means more as “$2.6 million a year”.
  • Claiming statistical methods you cannot explain in an interview, such as Bayesian models or causal forests used once.
  • Hiding the domain. A recruiter for an e-commerce role wants to see e-commerce words in the first few lines.
  • Dashboards counted by the dozen. Fifty dashboards nobody opens is not an achievement; one that runs a weekly meeting is.

Questions and answers

How do I show impact as a data analyst when others made the decision?

Describe your part honestly and then the result: “my analysis showed X; the team changed Y; Z happened”. Hiring managers know analysts rarely make the final call, and they want to see your work led somewhere.

Should a data analyst resume include a projects section?

Only if it shows something your job does not, such as modeling or a new tool. At mid-level, the space is usually better spent on your current role.

What is the difference between a data analyst and a business intelligence analyst resume?

Analyst resumes lean on questions answered, experiments and decisions. BI resumes lean on reporting platforms, data models, governance and the number of people served. See the business intelligence analyst example.

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