Data Analyst resume example

• Entry level

  Data analyst with a statistics degree and a year of experience at a healthcare nonprofit. Writes SQL queries against PostgreSQL, builds Tableau dashboards for program managers and automated a monthly report that saved 8 hours. Completed a Google Data Analytics certificate and is seeking a team where analysis directly shapes decisions.

• Mid level

  Data analyst with five years in ecommerce analytics. Uses SQL, Python and Looker to analyze funnel, retention and pricing, and delivered an analysis that lifted repeat purchase rate by 6%. Presents findings to marketing and product leaders and builds data checks that cut reporting errors by half.

• Senior

  Senior data analyst with nine years in subscription businesses. Leads analytics for growth and pricing, mentors three analysts and defines the company's core metrics with finance. Skilled in SQL, Python, experiment analysis and executive storytelling, with analyses credited for roughly $2M in annual revenue and cost improvements.

• Career changer

  Former retail operations lead moving into data analysis after two years of building the store network's weekly sales reports in Excel and SQL. Comfortable cleaning messy point-of-sale data, explaining a variance to a regional manager and turning a recurring question into a dashboard people actually open.

• Domain specialist

  Healthcare data analyst who knows claims, encounter and EHR data and the privacy rules around them. Builds Power BI reporting for clinical and finance teams, reconciles numbers across systems before anyone quotes them, and writes up methods so a second analyst can rerun the work.

• Graduate

  Statistics graduate with SQL, Python and Tableau coursework and a capstone that analyzed city bike-share demand. Looking for an entry-level data analyst role where I can own recurring reports and learn how the business uses them.

• Career changer

  Finance associate with four years of variance analysis and Excel modeling, now applying for data analyst roles. Bringing a habit of checking numbers twice and explaining them plainly, and adding SQL and Power BI from recent projects.

• Bootcamp

  Analytics bootcamp graduate with three portfolio projects in SQL and Python, including a churn analysis on a public telecom dataset. Seeking a junior analyst role on a team that reviews code and asks good questions.

• Showing tools but not decisions

  Fix: Anyone can list SQL and Tableau. Describe a question you answered and the action that followed, such as 'identified a pricing gap that led to a 3% revenue lift.' Decisions are the proof of impact.

• Writing 'proficient in Excel' as the only technical line

  Fix: State specific skills like pivot tables, XLOOKUP and Power Query, then add SQL joins or window functions and a BI tool. Hiring managers check for stack breadth and depth together.

• Ignoring data cleaning and validation

  Fix: Most analyst time goes to messy data. Mention the sources you cleaned, the checks you set up and the errors you caught, since stakeholders trust analysts who prove their numbers are right.

• Omitting the audience

  Fix: Say who consumed your analysis: marketing leads, a CFO, product managers. It shows communication skill and lets recruiters see whether you can present to the level they need.

Match these against the job posting you are applying to: the free resume checker shows which keywords your resume is missing.

SQL

Name the warehouse and the kind of query, such as cohort retention in BigQuery, in a bullet with its result.

Tableau / Power BI

Say who used the dashboard and what decision it supported, not only that you built one.

Python or R

Point to an analysis or an automation, such as a weekly report that now runs on its own.

A/B testing

Describe the test, the metric you read and the call the team made after it.

KPI reporting

List the metrics you owned and the audience that reviewed them.

Data cleaning

Mention the source you fixed and what stopped going wrong afterwards.

Stakeholder management

Name the teams you worked with, such as marketing or finance, and how often.

Forecasting

State the horizon and how close the forecast came, with a figure you can explain.

Data modeling

Mention tables or models you designed and who builds on them now.

ETL

Say which pipeline you maintained or built and the tools behind it.

• Analyzed 2 years of order data in SQL to find an underperforming shipping tier, and the pricing change that followed raised margin by 3 points.
• Built a Tableau dashboard used weekly by 30 managers, replacing 9 separate spreadsheets.
• Automated a monthly KPI report with Python and scheduled queries, saving about 14 hours of manual work each month.
• Ran cohort analysis showing that customers who used a key feature in week one retained 22% more, which changed the onboarding flow.
• Evaluated 18 A/B tests with proper sample size checks and flagged 3 invalid results before they influenced product decisions.
• Cleaned and merged 5 data sources totaling 4 million records, reducing duplicate customer entries by 31%.
• Forecasted weekly demand with a seasonal model that came within 7% of actual sales over the following quarter.
• Presented a churn analysis to the executive team that led to a $150K retention campaign and a 4% drop in cancellations.
• Created a data dictionary of 60 metrics that resolved recurring disagreements between finance and marketing.
• Taught SQL basics to 12 colleagues in four sessions, increasing self-service requests and reducing ad hoc ticket volume by about 25%.

• Mirror the posting's stack and questions

  Analyst roles differ more than the title suggests: one team wants SQL and Looker for product metrics, another wants Excel and finance reporting. Move the tools and the business questions the posting names to your summary and first bullets, and drop what it never mentions. Tailor your resume to the job

• Lead with one finding in the cover letter

  Open the letter with a short story of a question you answered, the data you used and what changed because of it. Then connect that to a problem the company is likely to have, and keep the letter under a page. Draft a cover letter for this posting

• Prepare a walkthrough of one analysis

  Interviews often include a SQL exercise and a case question. Practice explaining one project end to end: the question, how you checked the data, the method, the result and what you would do differently. Practice likely interview questions

• Link a small, readable portfolio

  If you are early in your career, one or two well-documented projects on GitHub or Tableau Public help more than a long list of courses. Put the link in your header and describe the project in one line on the resume.