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Data Analyst CV Bullet Points

Copy-paste CV bullet points crafted for Data Analyst roles. ATS-optimised examples with strong action verbs and quantifiable metrics.

Data & Analytics

How do you write Data Analyst CV bullet points?

Start each bullet with a strong action verb, say what you did, then show the result with a number: money saved, time cut, people helped or targets hit. Keep each to one or two lines and mirror the keywords in the job advert. Below are 4 Data Analyst examples you can adapt; swap in your own real figures.

As of October 2026. Updated .

4Bullet Points
7ATS Keywords
3Seniority Levels

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Experience Bullet Points

Experienceall levels

Built automated reporting dashboards in Tableau reducing manual reporting time by 20 hours/week

Builtmetrics included
Experienceall levels

Analysed customer behaviour data to identify £500K revenue opportunity in cross-selling

Analysedmetrics included
Experienceall levels

Presented insights to C-suite executives, influencing £1M+ strategic decisions

Presentedmetrics included
Experienceall levels

Developed SQL queries and Python scripts to process 10GB+ datasets daily

Developedmetrics included

ATS Keywords for Data Analyst

Include these keywords in your CV to improve ATS compatibility

SQLExcelData visualisationTableauPower BIPythonStatistical analysis

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Tips for Data Analyst CVs

Use Industry-Specific Terminology

Include keywords and phrases that are commonly used in Data & Analytics. This helps both ATS systems and hiring managers quickly identify your expertise.

Quantify Your Achievements

Wherever possible, add numbers to demonstrate your impact. Percentages, revenue figures, team sizes, and project timelines make your contributions concrete.

Tailor to Each Application

Use these bullet points as templates, but customise them for each job you apply to. Mirror the language and priorities from the job description.

Data Analyst CV FAQs

Emphasise SQL proficiency, Excel expertise, visualisation tools (Tableau, Power BI), and any programming skills (Python, R). Include experience with specific databases and BI platforms used in your target industry.
Connect your analysis to business outcomes: "Identified 5 key churn drivers, reducing churn by 15%" or "Built dashboards saving 20 hours/week for stakeholders". Always link insights to decisions or savings.
Yes, if possible. Link to Tableau Public dashboards, GitHub repositories with analysis projects, or a personal website showcasing your work. Visual examples of your analysis are compelling.
Highlight transferable analytical skills from your current role, any data-related projects, and relevant certifications (Google Analytics, Tableau). Emphasise domain knowledge that could be valuable.

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