Data analyst hiring managers want proof that you can find answers in messy data and explain them to non-technical people. The best CVs connect technical skills to business decisions.
Core skills to show
Data: SQL (PostgreSQL, BigQuery), Excel (Power Query, pivot tables, XLOOKUP)
Programming: Python (pandas, matplotlib), basic R
BI & visualisation: Power BI, Tableau, Looker Studio
Methods: data cleaning, A/B testing, cohort analysis, forecasting, KPI design
Bullets that connect data to decisions
- Built a Power BI sales dashboard used by 35 managers weekly, replacing 6 manual Excel reports.
- Analysed customer churn with SQL and Python, identifying a pricing issue that informed a change reducing churn by 12%.
- Automated data cleaning in Python, cutting report preparation from 2 days to 2 hours.
Data analyst profile examples
Economics graduate with the Google Data Analytics Certificate and three portfolio projects analysing public transport, retail and housing data with SQL and Power BI. Comfortable cleaning messy datasets and presenting findings clearly. Seeking a junior data analyst role.
Data analyst with 5 years in e-commerce, specialising in customer analytics and experimentation. Built the company's A/B testing reporting and a churn dashboard that informed a retention programme worth $1.4M a year.
Put this into practice
Build an ATS-friendly CV with live preview and free PDF download.
Describing a portfolio project on your CV
Retail Sales Analysis — SQL, Python, Power BI | github.com/yourname/retail-analysis
• Cleaned and joined 500K rows of transaction data from 3 sources
• Identified that 18% of revenue came from 2% of products; recommended stock changes
• Published an interactive dashboard with regional and product drill-downs
Mistakes to avoid
- Listing tools without showing what you did with them.
- Using vague results like "improved efficiency" — say how much, for whom.
- Linking to a portfolio with unfinished notebooks or no explanations.
- Over-claiming advanced machine learning skills for an analyst role that needs strong SQL and communication.
Portfolio projects for entry-level analysts
- Use public datasets (government open data, Kaggle) to answer a clear business question.
- Publish a dashboard and a short write-up of your findings.
- Show the full process: question, cleaning, analysis, visualisation, recommendation.
Start with our data analyst CV template and check the skills guide.
Frequently asked questions
Do I need Python for a data analyst job?+
Not always. SQL and Excel are the most common requirements; Python is increasingly valued and helps for more technical roles.
Are certifications useful?+
Certifications such as Google Data Analytics or Microsoft PL-300 (Power BI) can help entry-level candidates, especially with portfolio projects.
Related CV examples
BuildCVFast Editorial Team
This guide is written and reviewed by the BuildCVFast editorial team using current hiring practices, published employer guidance and official government sources where relevant. We update our guides regularly. Read our editorial policy or send us a correction.