Data analyst CV example
A data analyst's CV has to answer one question: which business decisions did your analysis change? Name the tools you use (SQL, Python or Power BI, for example) and explain what you achieved with them.
Below is an example of how to balance the technical side with business results, and the mistakes to avoid. If the person reading your CV works outside Lithuania, they will not know your employers, so a few words on what the company does, such as “a retail chain”, give your numbers their scale.
CV example
Data analyst at a retail chain: built a sales forecasting model that cut warehouse stock by 18% and a Power BI reporting system used daily by 60 managers.
- Built a demand forecasting model (Python, scikit-learn): warehouse stock down 18%, write-offs down 11%.
- Designed a set of Power BI reports for 60 managers, replacing manual Excel reports entirely.
- Optimised SQL queries in the data warehouse, cutting report generation time from 25 minutes to 3.
- Analysed advertising campaign data (Google Analytics, SQL) for 15 clients; average conversion rate up 12%.
- Automated weekly reports with Python scripts, saving 6 hours a week.
Vilnius University, Faculty of Economics and Business Administration: BSc,Quantitative Economics, 2020
What to put in a data analyst CV
Not “analysed sales data”, but “the analysis showed that 20% of products caused 80% of write-offs; changing the order frequency cut stock by 18%”.
Start with the ones you use every day (SQL, Python, Power BI), then the ones you have worked with occasionally. Use the job ad's keywords exactly as written (“Power BI”, not “PowerBI”): applicant tracking systems (ATS) and recruiters search for that spelling.
Link to GitHub, Kaggle or Tableau Public with one clear project: the question, the data, the method, the conclusion.
Companies want someone who can run an A/B test and also understands what a margin means. Show both through your achievements.
Most common mistakes
- A CV full of tools but without a single conclusion the business acted on.
- Mixing up the data analyst, data engineer and data scientist roles, so the CV is aimed at the wrong job.
- Training projects (Titanic, Iris) presented as work experience.
Frequently asked questions
Can I become a data analyst without a university degree?
Yes. On the Lithuanian job market a portfolio and SQL/Python skills matter more. A completed course (Google Data Analytics, Turing College and the like) plus 2–3 public projects often outweighs a degree.
How many tools should I list in my CV?
8–12, and only the ones you could talk about in an interview. A longer list raises suspicion.
Should I include training projects?
Yes, if you do not have real experience yet, but in a separate “Projects” section, not under work experience, and with a link to the code or the report.