What matters most on a data analyst's resume is the decision your analysis led to. Show how you framed the question and communicated the result to change something, more than the tools you used.
For: Candidates for data analyst and business analyst roles
Start with this example ↗All people, companies and numbers here are fictional. Replace them with your own experience.
Jiho Bae
Data Analyst · 4 years, commerce customer and marketing analytics
Advanced Data Analytics Semi-Professional (ADsP) · Korea Data Agency 2020-11
Education
Example University
2014-03 – 2020-02
Statistics · B.S. · Graduated
Summary
I have analyzed customer behavior and marketing performance in commerce for four years. I break questions down, check them with data and deliver conclusions in a form decision-makers can use right away.
Experience
Example Commerce · Data Analyst
2022-01 – Present
• Found the cause of falling repurchase through cohort analysis, leading to a decision to send coupons within 7 days of the first order.
• Unified revenue and active-user definitions into a dashboard, cutting weekly report prep from four hours to 30 minutes per team.
Example Research · Junior Data Analyst
2020-03 – 2021-12
• Cleaned client survey data and wrote cross-tabulation reports.
• Automated recurring Excel tallies with Python scripts, saving 20 hours a month.
Projects
Recommendation A/B Test Design · Experiment design · Analysis
2023-06 – 2023-08
SQL · Python · Statistical testing
• Designed sample size and duration and interpreted results, recommending holding a full rollout because clicks rose without a difference in purchases.
Three keys to a Data Analyst resume
01
From question to decision in one flow
A good case reads as: what was the question, which data confirmed it, and what changed as a result. With that flow in every line, you show analytical and business sense together.
02
Show tools inside the cases
Don't leave SQL, Python and BI tools only in the skills list; show how you used them inside each case. Context conveys your level far better.
03
Communication and automation are results
Dashboards, unified metric definitions and automated reports speed up decisions. Say how many people use them and how much time they save.
Writing the summary
Write your data domain (marketing, product, operations and so on) and strengths in one or two sentences. Summarize one case where analysis led to a real decision.
I have analyzed customer behavior and marketing performance in commerce for four years. I break questions down, check them with data and deliver conclusions in a form decision-makers can use right away.
Try rewriting it like this
BeforeExtracted and analyzed data with SQL.
AfterInvestigated a drop in repurchase with SQL cohort analysis and found customers who got a coupon within 7 days of their first order repurchased twice as often, which led to changing coupon timing.
Show the question, the finding and the decision that changed, not the tool.
BeforeBuilt dashboards.
AfterUnified revenue and active-user definitions that differed by team into a Tableau dashboard, cutting weekly report prep from four hours to 30 minutes per team.
Who uses the dashboard and what changed is the result.
BeforeAnalyzed A/B tests.
AfterDesigned sample size and duration for a recommendation A/B test and interpreted it, showing clicks rose but purchases did not, which put a full rollout on hold.
Analysis that stops a decision is also a result.
Organizing skills
Group skills into extraction and processing (SQL, Python), visualization and BI (Tableau, Looker Studio) and statistics and experiments (A/B testing, regression). Put certifications in their own section as supporting evidence.
What changes with experience
If this is your first application
As a new analyst, present two or three cases from public data or projects as question, method and conclusion. Links to code and reports help a lot.
If you have more experience
Later, lead with organization-level changes such as metric frameworks, pipeline improvements and spreading an analysis culture. Keep individual analyses to a few key cases.
Common mistakes
No mention of the decision the analysis led to
Listing libraries you do not use
Internal metric names without explanation
Case descriptions that never mention limits or assumptions
Frequently asked questions
Can I apply without a related degree?
Yes, if you have analysis projects and outputs. Lead with times you solved problems with data in previous roles.
Which matters more, Python or SQL?
Most analyst roles treat SQL as a baseline. Python is a strength when paired with automation or statistical modeling examples.
Do certifications help?
Certifications like SQLD or ADsP are supporting evidence of fundamentals. Real analysis cases matter more.
Build your resume from this example
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