Free Mid-level data analyst CV (2026)

Format: Keep the CV to one page if you have up to five years' experience in data analytics, and two pages if you have more extensive project work or leadership responsibilities. Use an A4 page layout with a clean, readable font (Calibri or Arial) in 10-12pt, with consistent spacing and clear section headings so your CV reads well on screen and in print.

Layout and margins: Use standard UK margins and avoid dense blocks of text so recruiters and applicant tracking systems can parse keywords.

Save the file as PDF unless the job advert requests another format, and name the file with your surname and forename (e.g. Smith_Jon_CV.pdf).

ATS and readability: Many UK employers use applicant tracking systems; include conventional headings (Experience, Skills, Education) and avoid overly fancy formatting.

Include two to three keywords from the job description in your CV where appropriate. Length expectations: One page for up to five years' experience; two pages for more extensive project work or leadership responsibilities.

Notes: In the UK, avoid including a photo or date of birth on standard CVs; for NHS/public sector roles you may encounter different recruitment conventions; check the job advert. Ensure you do not include sensitive personal data beyond contact details and right-to-work status.

Put your name at the top in a larger font, followed by a UK phone number, a professional email address, and a short link to your LinkedIn profile or CV portfolio that demonstrates your analyses. Do not include unnecessary personal details (date of birth, age, marital status, or a photo).

Ensure the contact information is current so UK employers can reach you easily.

If you link to a portfolio, include two to four polished examples with short descriptions, data sources, and code or dashboards where relevant. Make sure public links work and your GitHub or dashboard permissions allow reviewers to view the work.

Also consider noting your right-to-work in the UK (or visa status) if applicable.

Write a two- to three-sentence professional profile that states your role (data analyst), years of UK experience (two to five), and the main tools you use (e.g. SQL, Python, R; Tableau or Power BI).

Emphasise the problems you solve and the sectors you've supported (e.g. NHS, financial services, retail) so the reader quickly understands your fit for the role.

Avoid vague buzzwords; mention one or two concrete achievements (e.g. improved a KPI or automated a reporting process). This concise profile helps a recruiter decide whether to read your experience section in more depth.

List roles in reverse chronological order; for each job provide your job title, employer, location (UK city), and dates in DD/MM/YYYY format. Under each role, include three to five bullet points starting with a strong action verb; describe what you did, how you did it, and the outcome.

Use the STAR approach; keep bullets focused and quantifiable where possible (e.g. improved data pipeline speed by 40%). If you cannot provide exact numbers, describe the scale (e.g. processed thousands of records per day).

Emphasise impact on business metrics and stakeholder outcomes. For NHS or public sector roles, consider referencing relevant pay bands or scheme levels when discussing roles and responsibilities.

List qualifications in reverse chronological order. Include institution, degree or certification, subject, and dates (DD/MM/YYYY).

In the UK, list GCSEs and A‑levels (with grades) if early in your career; for higher-level roles, include degree results (classification). If you studied at a UK university, mention UCAS points or admission route if relevant, especially when applying to Russell Group institutions.

If you studied abroad, provide country and any UK equivalences. Include professional certifications relevant to the role (e.g. data protection/compliance, NHS analytic training).

For NHS/public sector roles, note any framework pay scales or bands when describing responsibilities.