Writing a Data Analyst CV

What Makes a Strong Data Analyst CV

A data analyst CV must do two things: pass an ATS (Applicant Tracking System) scan and convince a hiring manager to call you. Most CVs fail at one or both. Understanding the constraints helps you write one that works.

Hiring managers for analyst roles spend an average of 6-10 seconds on initial CV review. Your most important information must be visible immediately and your bullets must be written in the language of outcomes, not tasks.

CV Structure for Data Analysts

The optimal structure for a data analyst CV:

1. Name and Contact Information
   - Full name
   - Email address (professional -- firstname.lastname@domain)
   - LinkedIn URL (customise it: linkedin.com/in/firstname-lastname)
   - GitHub URL (link to your portfolio)
   - Location (city, country -- no need for full address)

2. Summary (3-4 lines max)
   - Who you are professionally
   - Core technical skills
   - What kind of role/impact you are targeting

3. Skills
   - Organised by category (Languages, Tools, Concepts)
   - Only list skills you can comfortably discuss in an interview

4. Experience (most recent first)
   - Company, role, dates
   - 3-5 bullets per role, outcome-focused

5. Projects (if limited work experience)
   - Project name, brief description
   - Link to GitHub or portfolio

6. Education
   - Degree, institution, year
   - Relevant modules or dissertation if applicable

7. Certifications (optional)
   - Google Data Analytics, Microsoft PL-300, etc.

Writing Impact-Focused Bullets

The most common CV weakness: describing tasks instead of outcomes.

Task-focused (weak):

• "Responsible for creating weekly sales reports"
• "Helped the team understand customer data"
• "Worked with SQL to query databases"

Outcome-focused (strong):

• "Built an automated weekly sales reporting pipeline in SQL + Python, reducing report preparation time from 4 hours to 15 minutes"
• "Identified a customer segmentation error that had misclassified 12% of accounts, correcting £340,000 in projected revenue"
• "Developed SQL queries to surface customer churn risk scores, enabling the retention team to prioritise outreach and reduce 90-day churn by 18%"

The formula: Action verb + what you did + quantified result or business impact.

Action verbs for data analysts:
Analysed, Developed, Built, Designed, Identified, Automated,
Reduced, Improved, Presented, Implemented, Standardised,
Translated, Surfaced, Modelled, Forecasted, Investigated

Quantifying Your Impact

If you have not tracked your metrics at work, reconstruct them:

• How long did the old process take vs the new one?
• How many people or teams use the dashboards you built?
• What was the dataset size you worked with?
• Did your analysis inform a decision? What was the decision worth?

Even small quantifications strengthen your bullets:

• "Built 6 executive dashboards used by 3 departments"
• "Reduced data preparation time by 60%"
• "Analysed a dataset of 2.4 million customer records"

Skills Section: What to Include

List only skills you can genuinely discuss in an interview. A skills section that lists 25 tools and frameworks suggests padding, not expertise.

SKILLS

Languages: SQL (PostgreSQL, BigQuery), Python (pandas, NumPy, matplotlib, seaborn)
Visualisation: Power BI (DAX, data modelling), Tableau, Matplotlib
Tools: Excel (VLOOKUP, pivot tables, Power Query), Git, Jupyter Notebooks
Databases: PostgreSQL, MySQL, Google BigQuery, Snowflake
Statistical: Hypothesis testing, regression analysis, A/B testing
Concepts: ETL pipelines, data cleaning, EDA, cohort analysis, dashboard design

Categorising skills by type makes scanning easier for technical reviewers.

Tailoring Your CV to Each Role

Do not send the same CV to every role. Spend 15-20 minutes per application tailoring:

1. Mirror the job description language. If they say "stakeholder management," use that phrase. ATS systems look for keyword matches.

2. Reorder your bullets. Put the experience most relevant to that role first.

3. Adjust your summary. Each summary should reflect the specific role and company type.

Example summary tailoring:

For a product analytics role: "Data analyst with 2 years of experience in B2B SaaS, specialising in user behaviour analysis, funnel optimisation, and A/B testing. Proficient in SQL, Python, and Mixpanel. Looking to apply product analytics skills to help [Company] improve user activation and retention."

For a financial services role: "Data analyst with strong SQL and Excel skills, experienced in financial reporting and risk data analysis. Comfortable working with large structured datasets, validating data quality, and presenting findings to senior stakeholders."

ATS Optimisation

Applicant Tracking Systems filter CVs before human review. To pass:

• Use standard section headings (Experience, Education, Skills -- not creative alternatives)
• Avoid tables and graphics that ATS cannot parse
• Include exact keywords from the job posting
• Submit as a PDF unless the posting specifies otherwise
• Keep formatting simple: one column, standard fonts (Arial, Calibri, Georgia)

What to Avoid

• Objective statements ("I am seeking a challenging role...") -- use a Summary instead
• Irrelevant experience that does not connect to data skills. Either omit it or reframe bullets to show transferable skills
• Soft skill padding ("team player," "detail-oriented") without evidence
• Long paragraphs -- bullets only in the experience section
• Photos, graphics, or infographic CVs -- they fail ATS and distract reviewers
• CVs over 2 pages for entry to mid-level roles

Key Takeaways

• Hiring managers spend 6-10 seconds on initial review. The most critical information -- role, key skills, and top achievement -- must be immediately visible.
• Write outcome-focused bullets using the formula: action verb + what you did + quantified business impact. Tasks describe effort; outcomes demonstrate value.
• Tailor your CV to each role. Mirror job description language for ATS and reorder bullets to highlight the most relevant experience first.
• List only skills you can confidently discuss in an interview. A credible, concise skills section is more effective than a comprehensive one that is only partially true.
• Keep CVs to two pages maximum for entry to mid-level roles. Remove anything that does not directly support your candidacy for this specific role.

Practice Exercise

CV Bullet Rewriting Exercise:

Rewrite these weak, task-focused bullets as strong, outcome-focused ones.
Use the formula: Action verb + what you did + quantified result.

1. "I was responsible for making reports for the sales team each week"
   Rewrite: ___________

2. "Helped clean the data before it was used for analysis"
   Rewrite: ___________

3. "Used SQL to pull data from the database"
   Rewrite: ___________

4. "Made a dashboard for the management team"
   Rewrite: ___________

5. "Analysed customer feedback"
   Rewrite: ___________

Sample strong versions (compare yours):
1. "Built automated weekly sales performance reports in SQL, saving the sales team 3 hours per week and enabling same-day insight delivery"
2. "Standardised data cleaning process for 500,000-row customer dataset, resolving 14% duplicate rate and improving downstream analysis accuracy"
3. "Developed SQL pipeline to extract, join, and aggregate 5 tables across 3 databases, reducing analyst query time by 70%"
4. "Designed executive dashboard in Power BI tracking 12 KPIs across 4 business units, used in weekly leadership reviews"
5. "Analysed 8,000 customer feedback responses using NLP keyword extraction, identifying 3 priority product issues that were actioned in the next sprint"