Data Analyst CV Example
A data analyst CV should highlight your ability to collect, process, and analyse data to uncover insights that drive informed business decisions and operational improvements.
Recommended template: Modern
Key Skills to Include
Quick Tips
- Include specific examples of analyses that led to actionable business decisions.
- Highlight your proficiency with key tools and languages with concrete project examples.
- Demonstrate your ability to communicate data insights to non-technical audiences.
- Mention any data governance or quality improvement contributions you have made.
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Start with the Modern template and customise it for your business operations role.
How to Write Your Data Analyst CV
A data analyst CV should showcase your technical skills, analytical thinking, and ability to turn data into business value. Employers want to see that you can work with large datasets, use the right tools for the job, and communicate insights clearly to non-technical audiences. Whether you specialise in marketing analytics, financial reporting, or operational intelligence, your CV should demonstrate both your technical proficiency and your impact on business decisions.
CV Structure
Use a reverse-chronological format with a clear profile, followed by work experience, technical skills, education, and certifications. For each role, describe the data environment you worked in, the tools you used, and the types of analysis you performed. Follow with quantified achievements that demonstrate the business value of your work. Include a dedicated technical skills section that lists your tools, languages, and proficiency levels.
CV Format
Choose a clean, modern template that allows you to display both narrative experience and technical skills clearly. A two-column layout can work well for separating skills from experience. Avoid cluttered designs and ensure the document is easy to scan. Use consistent formatting for tool names and technical terms throughout.
CV Profile Examples
Senior Data Analyst
Analytical and detail-oriented data analyst with six years of experience transforming complex datasets into actionable business insights across retail and financial services sectors. Proficient in SQL, Python, and Power BI with a track record of building automated reporting solutions that saved over 200 hours of manual work annually. Skilled at communicating findings to senior stakeholders to inform strategic decisions.
Data Analyst — Marketing
Results-focused data analyst specialising in marketing analytics, with four years of experience measuring campaign performance, customer segmentation, and attribution modelling. Expert in Google Analytics, SQL, and Tableau with strong statistical skills. Passionate about using data to optimise marketing spend and improve customer acquisition efficiency for B2C businesses.
Junior Data Analyst
Enthusiastic data analyst with a BSc in Mathematics and eighteen months of commercial experience in a fast-paced e-commerce environment. Proficient in SQL, Excel, and Power BI with a developing knowledge of Python for data manipulation. Eager to deepen analytical skills and contribute to data-driven decision-making within a collaborative analytics team.
State your years of experience, key technical skills, and the sectors you have worked in. Mention one or two headline achievements that quantify the business value of your analytical work. Keep the profile to three or four sentences.
Key Skills for Your Data Analyst CV
Data Analysis & Visualisation
Exploring datasets to identify patterns and presenting findings through clear charts, dashboards, and reports.
SQL
Writing complex queries to extract, join, and transform data from relational databases for analysis and reporting.
Python / R
Using programming languages for data manipulation, statistical analysis, and building automated analytical workflows.
Power BI / Tableau
Building interactive dashboards and reports that enable stakeholders to explore data and monitor key metrics.
Excel (Advanced)
Using advanced functions including pivot tables, VLOOKUP, INDEX-MATCH, and VBA macros for data analysis.
Statistical Analysis
Applying statistical methods such as regression, hypothesis testing, and correlation analysis to draw reliable conclusions from data.
ETL Processes
Extracting, transforming, and loading data from multiple sources into structured formats suitable for analysis.
Report Automation
Automating recurring reports using scripts and scheduling tools to eliminate manual effort and improve timeliness.
Data Quality Management
Identifying and resolving data quality issues to ensure accuracy and reliability of analytical outputs.
Work Experience Examples
For each role, describe the data environment — volume, tools, and team structure. Highlight specific analyses you performed and the business decisions they informed. Quantify your impact wherever possible — cost savings, revenue increases, time reductions, or accuracy improvements. Mention the stakeholders you presented to, as this demonstrates your communication skills.
Data Analyst
Clearview Retail Analytics
Provided analytical support across merchandising, marketing, and operations teams for a £350M multi-channel retailer, working with datasets of over 10 million transaction records.
Responsibilities
- Built and maintained Power BI dashboards tracking sales performance, inventory levels, and customer behaviour across 120 stores and online channels.
- Wrote complex SQL queries to extract, transform, and analyse data from the company's data warehouse for ad-hoc reporting and scheduled reports.
- Developed a customer segmentation model using Python that informed targeted marketing campaigns and loyalty programme design.
- Automated weekly and monthly reporting processes using Python scripts, reducing manual reporting effort by 15 hours per week.
- Presented analytical findings and recommendations to senior leaders at monthly trading review meetings.
Achievements
- Built a demand forecasting model that reduced overstock by 18%, saving £1.2M in markdown costs during the autumn-winter season.
- Identified a pricing anomaly through data analysis that recovered £85,000 in revenue within two weeks of implementation.
- Reduced report generation time from four hours to twenty minutes by automating the weekly trading report using Python and Power BI.
Junior Data Analyst
Braeburn Financial Services
Supported the business intelligence team in producing management information and performance reports for a consumer lending company.
Responsibilities
- Created and maintained Excel-based management reports tracking loan portfolio performance, arrears, and collections activity.
- Queried the SQL Server database to extract data for monthly regulatory returns and board reporting packs.
- Assisted senior analysts with ad-hoc analysis requests from marketing, risk, and operations teams.
- Participated in the implementation of a new Power BI reporting platform, migrating legacy Excel reports to interactive dashboards.
Achievements
- Successfully migrated 12 legacy Excel reports to Power BI, improving data accuracy and reducing manual effort by 20 hours per month.
- Identified a data quality issue in the collections reporting that, once corrected, improved the accuracy of arrears reporting by 8%.
Education & Qualifications
List your degree — particularly if it is in a quantitative subject such as mathematics, statistics, computer science, or economics. Include any data analytics certifications or professional courses such as Google Data Analytics, Microsoft Power BI, or DataCamp programmes.
Google Data Analytics Professional Certificate
A widely recognised programme covering data analysis fundamentals using spreadsheets, SQL, R, and Tableau.
Microsoft Certified: Power BI Data Analyst Associate
A Microsoft certification validating proficiency in building and optimising Power BI solutions.
BSc Mathematics / Statistics / Computer Science
A quantitative degree providing the analytical foundation valued by data analytics employers.
Python for Data Science (DataCamp / Coursera)
Online certification demonstrating practical Python skills for data manipulation and analysis.
Frequently Asked Questions
What technical skills are most important for a data analyst CV?
How do I demonstrate business impact on a data analyst CV?
Should I include a portfolio or GitHub link on my data analyst CV?
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