5 CV examples · UK · Updated October 2026
Data Analyst CV Examples and Templates (UK)
A strong data analyst CV proves you turn messy data into decisions. Name your tools (SQL, Excel, Power BI, Python or R), give the scale of the data you handle and show what changed because of your analysis. Open with a short personal profile, not an objective.
Data Analyst CV at a glance
- Best format
- Reverse-chronological, single column, profile and technical skills first
- Length
- 1 page for juniors; 2 pages after five years in data
- Top skills
- SQL and Excel, Power BI or Tableau, Python or R, Data cleaning and validation
- Key qualifications
- Numerate degree or data apprenticeship, Microsoft Power BI Data Analyst (PL-300), Google Data Analytics or similar certificate
- Average salary
- £28,000 to £65,000 a yearstarter to experienced, National Careers Service
- Typical hours
- 37 to 40 a weekbetween 8am and 6pm
5 data analyst CV examples for 2026
Below are 5 UK data analyst CV examples, from a graduate with one internship to a lead analyst, plus personal profiles, skills, bullet points, ATS keywords and a free data analyst CV template in Word for every example. Each one is shown at true A4 size and comes with a free single-column Word template. Open any example to read it in full.
Swipe to see all 5 examples →
Ruth Adomako
Graduate Data Analyst
Sheffield · ruth.adomako@email.com · 07700 900238 · linkedin.com/in/ruth-adomako-cv238
Skills & Tools
Personal Profile
Economics graduate (BSc Hons, 2:1) with a ten-week data internship at a Sheffield energy consultancy, cleaning smart meter data in SQL and building Power BI reports. Uses Python (pandas) and R to analyse public data, including ONS releases. Seeking a graduate data analyst role with structured training and mentoring.
Employment History
Data Analyst Intern, Tallowmere Energy Consulting, Sheffield Jun 2025 – Aug 2025
- Cleaned 14 months of half-hourly meter data for 62 sites in SQL, fixing gaps and duplicate reads.
- Built a Power BI report comparing each site’s energy use with its baseline, used by four account managers in monthly client reviews.
- Automated a three-hour weekly meter ID check against the client register with a Python script.
- Showed the operations director evidence of overnight and weekend energy waste, leading to heating timer changes at nine client sites.
Data Lead (volunteer), University Volunteering Society, Sheffield Sep 2024 – Jun 2026
- Moved 400 paper sign-ups into a validated Google Sheets tracker with a volunteer hours dashboard.
- Analysed attendance by project and term, showing the committee which session times lost volunteers after week four of each term.
- Applied the society’s data protection rules, restricting access to members’ contact details and deleting leavers’ records every summer.
Customer Assistant (part-time), Ashmorley Foodstores, Sheffield Oct 2022 – Present
- Balance tills and complete cash-up sheets on weekend shifts, working accurately with figures.
- Log chilled waste weekly, helping the section manager cut over-ordering on short-dated lines.
- Train new starters on the till, refunds and Challenge 25 age checks during Christmas and summer peaks.
Education & Qualifications
BSc (Hons) Economics, University of Sheffield, 2:1, 2026
Dissertation (First): bus service cuts and youth unemployment, modelled in R with ONS data
A-levels: Mathematics (A), Economics (A), Geography (B), 2023
Google Data Analytics Professional Certificate, 2025
Portfolio projects
- MOT failures (GitHub): ranked brake failures by car model and age using DVSA MOT data in Python.
Why this example works
- Treats a ten-week internship like a real job, with data volumes, tools and an outcome a hiring manager can check.
- Shows SQL, Python, R and Power BI in use rather than just listed, which is what graduate data analyst screening looks for.
- Uses UK public data (ONS, DVSA) in the dissertation and portfolio, proving initiative beyond coursework and a single internship.
Why this example works
- Shows the apprenticeship route clearly, so employers see formal training alongside three years of delivered reporting.
- Uses the terms housing employers screen for: Tenant Satisfaction Measures, Awaab’s Law, damp and mould, arrears and stock condition.
- Frames five contact centre years as an asset: first-hand knowledge of how customer data is captured and where errors start.
Applying through an online portal? Use the Word download: it is the same CV in a single-column, ATS-safe layout. Keep this two-column design for emailing and networking.
Rajan Bhogal
Business Intelligence Analyst
Northampton · rajan.bhogal@email.com · 07700 900684 · linkedin.com/in/rajan-bhogal-cv684
Profile
Business intelligence analyst with eight years in data roles across logistics and retail, now owning the Power BI estate for a 2,400-employee third-party logistics firm with 11 UK warehouses. Designs star-schema semantic models, writes DAX and T-SQL, and runs reporting on Microsoft Fabric. Microsoft PL-300 and DP-600 certified. Seeking a senior BI analyst or BI lead role.
Employment History
Business Intelligence Analyst, Nenford Logistics, Northampton Mar 2023 – Present
- Own 40 Power BI reports and six shared semantic models used by 380 managers across every warehouse and the transport office.
- Led the 2025 migration from on-premises SQL Server to Microsoft Fabric, retiring 120 nightly SSIS packages without a missed refresh.
- Built a dock-to-stock and OTIF dashboard that exposed carrier delays, supporting contract renegotiations with three hauliers.
- Introduced row-level security so each client sees only its own stock and orders, passing two client data protection audits.
- Cut average model refresh time from 48 to 9 minutes by redesigning models as star schemas and removing calculated columns.
Data Analyst, Hartlemoor Home Retail, Milton Keynes Jun 2020 – Feb 2023
- Produced weekly trading packs for 85 stores in Power BI, replacing a 30-tab Excel workbook emailed every Monday.
- Analysed click-and-collect demand by postcode, choosing 12 stores for extra lockers.
- Wrote T-SQL views on the sales data warehouse so buyers could self-serve margin and stock cover by supplier.
- Ran price elasticity analysis on 300 seasonal lines, helping merchandisers plan markdowns that cleared stock two weeks sooner.
- Documented 60 KPI definitions in a shared data dictionary, ending disputes between finance and trading over sales figures.
Junior MI Analyst, Wootonbrook Distribution, Northampton Sep 2018 – May 2020
- Compiled daily pick, pack and despatch reports from the warehouse management system for shift managers at a 24-hour site.
- Built an Excel model forecasting weekly labour hours from order volumes, adopted for booking agency staff in peak.
- Investigated stock discrepancies with the inventory team, tracing a recurring error to one barcode scanning step.
- Learnt SQL on the job and took over the site’s Access database queries.
Warehouse Operative (seasonal), Online retail fulfilment centre, Northampton Jun 2015 – Aug 2017
- Picked and packed orders during summer and Christmas peaks while at university, meeting pick-rate targets on handheld scanners.
- Reported damaged stock and mislabelled locations to team leaders, helping the shift keep pick accuracy above target.
- Saw how scanner data set every shift’s targets, the interest that led to a junior MI role after graduating.
Education & Qualifications
BSc (Hons) Mathematics, University of Leicester, 2:1, 2018
A-levels: Mathematics (A), Further Mathematics (B), Physics (B), 2015
Training & Certificates
Microsoft Certified: Power BI Data Analyst Associate (PL-300), renewed 2026 · Microsoft Certified: Fabric Analytics Engineer Associate (DP-600), 2025
Technical Skills
Power BI (DAX, Power Query M) · Microsoft Fabric lakehouses and warehouses · Star schema data modelling · T-SQL and Azure SQL Database · Row-level security and governance · Deployment pipelines and Git · Data Factory and SSIS · Python for data preparation · Warehouse KPIs (OTIF, pick rates) · Requirements workshops
Technical
Power BI · Microsoft Fabric · Azure SQL · SQL Server · SSIS · Data Factory · Python · DAX Studio · Tabular Editor · Git · Excel
Key projects
- Carbon reporting (2024): built the Power BI model behind the firm’s Streamlined Energy and Carbon Reporting disclosure, combining fleet fuel and site energy data.
- Self-service rollout (2025): trained 60 operations managers to build their own reports on certified semantic models, cutting ad hoc report requests by a third.
- Returns analysis (2023): linked carrier, reason and product data for an online retail client, showing six product lines caused 40% of its returns.
Community and training
- Co-organiser of a Midlands Power BI user group (2024 – Present), running quarterly meetups and presenting a session on DAX performance tuning.
- Wrote the company’s Power BI accessibility guidance on colour contrast, alt text and keyboard navigation for 25 report authors.
- Microsoft Learn paths in Fabric data engineering and Python for data analysis (2025); annual data protection and information security training.
Why this example works
- Opens with the scale of the BI estate (reports, models, users, sites), which is how a BI lead judges scope.
- Names modelling and governance work, such as star schemas, row-level security and Fabric, that separates a BI analyst from a report builder.
- Shows a clear progression from MI reporting at a warehouse to owning a company-wide Power BI platform.
Why this example works
- Names the NHS data sets and systems Band 6 and Band 7 shortlisting panels look for: ECDS, SUS+, RTT, SNOMED CT, SSRS and Power BI.
- Shows impact on patient flow, not just reports: data quality raised, a same day emergency care business case and earlier long-waiter alerts.
- Lays out Band 5 to Band 6 progression and supervision, matching a principal analyst person specification.
Joel Fung
Lead Data Analyst
Edinburgh · joel.fung@email.com · 07700 900815 · linkedin.com/in/joel-fung-cv815
Profile
Lead data analyst with 12 years in insurance and banking analytics, managing a team of six at an Edinburgh general insurer with 1.4 million home and motor policies. Owns pricing and claims insight, Consumer Duty outcome monitoring and the move to a cloud data platform. Builds analysis in SQL, Python and dbt, and turns it into decisions for the executive committee. Seeking a head of analytics role.
Employment History
Lead Data Analyst, Pentlandmuir Insurance, Edinburgh Jan 2022 – Present
- Lead the pricing, claims and customer insight analysts, owning hiring, objectives and a fortnightly code review.
- Designed a dashboard tracking the four Consumer Duty outcomes (products and services, price and value, consumer understanding, consumer support), split for customers with characteristics of vulnerability.
- Wrote the analysis behind the insurer’s first annual Consumer Duty board report in 2024, including fair value testing across 14 products.
- Migrated 300 legacy SQL reports to tested, documented dbt models on Snowflake, cutting monthly MI production from eight days to two.
- Found that claims from customers flagged as vulnerable took 40% longer to settle, prompting a dedicated claims handling team.
- Manage a £420,000 analytics budget, including data vendor contracts for vehicle and property risk data.
Senior Data Analyst, Pentlandmuir Insurance, Edinburgh Mar 2019 – Dec 2021
- Built a renewal retention model in Python to support pricing changes needed before the FCA’s home and motor renewal pricing rules took effect in January 2022.
- Analysed fraud referrals with the counter-fraud team, raising the hit rate of investigated referrals from 18% to 31%.
- Created a self-service Tableau suite for 90 underwriters and claims managers, replacing 40 emailed spreadsheets.
- Designed A/B tests on online quote journeys, with the winning layout lifting quote-to-buy conversion by 1.8 percentage points.
- Coached three junior analysts on SQL and statistics, two of whom were promoted within 18 months.
Data Analyst, Leithmount Bank, Edinburgh Aug 2016 – Feb 2019
- Analysed mortgage arrears by region and product for the collections strategy team, presenting monthly to the head of collections.
- Built SQL Server stored procedures feeding the credit risk MI pack reviewed by the credit committee.
- Mapped customer data fields across 12 marketing tables for the 2018 GDPR programme, removing personal data with no lawful purpose.
- Automated a weekly complaints root-cause report in R, saving the complaints team a day each week.
Graduate Analyst, Glenkelvie Insurance Brokers, Glasgow Sep 2014 – Jul 2016
- Prepared monthly commercial insurance portfolio reports in Excel and Access for account executives at a 200-person broker.
- Cleaned and merged client records from two acquired brokers, removing 4,000 duplicates before migration.
- Learnt SQL and VBA to automate renewal lists, cutting a two-day monthly task to two hours.
Customer Adviser (part-time), Bank contact centre, Edinburgh Sep 2010 – May 2013
- Answered current account and card queries on evening and weekend shifts while studying, meeting call quality targets.
- Logged complaint reasons accurately in the case system, an early lesson in how front-line data quality shapes management information.
Education & Qualifications
MSc Statistics, University of Glasgow, 2014
BSc (Hons) Mathematics, University of Edinburgh, 2:1, 2013
Training & Certificates
Chartered Statistician (CStat), Royal Statistical Society (2021) · ILM Level 5 Certificate in Leadership and Management (2023)
Technical Skills
Analytics team leadership · Consumer Duty outcomes reporting · Pricing and claims analytics · Customer segmentation and retention · Experiment design and A/B testing · SQL (Snowflake, SQL Server) · Python (pandas, scikit-learn, statsmodels) · dbt and analytics engineering · Tableau and Power BI · Data governance and quality frameworks · Board and executive reporting · Hiring and coaching analysts · Vendor and budget management
Technical
Snowflake · dbt · SQL Server · Python · R · Tableau · Power BI · Git · Azure DevOps · Excel
Speaking and volunteering
- Speaker at an Edinburgh analytics meetup on testing dbt models in regulated firms (2025).
- STEM Ambassador (2019 – Present): run data skills sessions for S5 and S6 pupils in Edinburgh secondary schools.
Professional development
- Royal Statistical Society CPD on causal inference and experiment design (2025); internal Consumer Duty training for analytics and pricing leads (2023).
Languages
- English (native) and Cantonese (fluent)
Why this example works
- Leads with team size, policy volumes and executive exposure, which is how a hiring panel judges a head of analytics candidate.
- Ties analysis to UK regulation, from Consumer Duty to the FCA renewal pricing rules and GDPR, which financial services employers prize.
- Shows modern tooling (Snowflake, dbt, Python) alongside leadership, proving the candidate still understands the work they manage.
Data Analyst personal profile examples
Copy the personal profile that matches your level, then swap in your own experience, settings and results.
Mathematics graduate (2:1) with a final-year project forecasting hospital admissions in R and a portfolio of three SQL and Power BI projects using data.gov.uk releases. Two years of part-time retail work have built accuracy and calm under pressure. Seeking a junior data analyst role in an experienced analytics team.
Operations team leader moving into data after six years running rotas, KPIs and weekly performance reports for a 50-person distribution shift. Built the site’s absence and productivity tracker in Excel and recently completed the Google Data Analytics Professional Certificate. Seeking a junior data or MI analyst role where operational knowledge adds value.
Data analyst with three years in ecommerce, writing SQL in BigQuery and building Looker Studio and Power BI dashboards used by trading and marketing teams. Automated weekly reporting with Python and ran A/B tests on checkout changes. Seeking a data analyst role with more ownership of analysis and stakeholder decisions.
Information analyst (Band 5) with two years in an NHS community trust, reporting on waiting lists, caseloads and contacts from SystmOne extracts using SQL Server and Power BI. Comfortable with information governance and Freedom of Information requests. Seeking a Band 6 analyst post in an acute trust or integrated care board.
Senior data analyst with nine years in retail and utilities, leading a team of four and owning customer analytics for 2 million accounts. Moved reporting onto Snowflake and dbt and introduced code review and testing standards. Experienced in presenting to executives. Seeking a lead analyst or analytics manager role.
Best skills for a data analyst CV
List the skills the job advert and person specification name, in the same wording, and prove the important ones in your employment history.
Hard skills
- SQL (joins, CTEs, window functions)
- Data cleaning, validation and quality checks
- Excel (pivot tables, XLOOKUP, Power Query)
- Dashboard design and data visualisation
- Descriptive and inferential statistics
- Regression and forecasting
- Data modelling (star schema)
- KPI definition and performance reporting
- A/B testing and experiment design
- Python (pandas) or R (tidyverse)
- Data protection and secure data handling
- Reproducible analysis with version control
Soft skills
- Explaining findings to non-specialists
- Questioning requirements before building
- Attention to detail
- Persistence with messy data
- Prioritising competing requests
- Working independently and in a team
- Presenting to senior leaders
Systems and equipment
- Microsoft Excel and Power Query
- SQL Server, PostgreSQL or MySQL
- Power BI (DAX) or Tableau
- Python (Jupyter, pandas) or R (RStudio, tidyverse)
- Cloud platforms: Microsoft Fabric, Azure, BigQuery or Snowflake
- Git with GitHub or Azure DevOps
- Google Analytics 4 and Looker Studio for marketing analysis
- Alteryx or KNIME in some teams
Qualifications and training
- Data Analyst Level 4 apprenticeship (England)
- Data Technician Level 3 apprenticeship (England)
- Microsoft Certified: Power BI Data Analyst Associate (PL-300)
- Microsoft Certified: Fabric Analytics Engineer Associate (DP-600)
- Salesforce Certified Tableau Data Analyst
- Google Data Analytics Professional Certificate
- Royal Statistical Society recognition: Data Analyst, GradStat or CStat
Data Analyst CV bullet point examples
Strong bullets pair an action verb with a specific task and a measurable result. Adapt these to your own numbers.
Data cleaning and quality
- Deduplicated 86,000 customer records across three legacy systems, agreeing match rules with the CRM owner before the merge.
- Set up automated SQL checks on nightly loads that flag missing postcodes and negative values before reports refresh.
- Traced a 12% drop in reported website conversions to a broken tag, restoring three weeks of figures from server logs.
Reporting and dashboards
- Built a Power BI field service dashboard showing engineer utilisation and missed appointments, adopted by six regional managers.
- Created a Looker Studio report linking donations to campaign source, showing trustees two appeals that cost more to run than they raised.
- Cut a monthly board pack from 60 pages to 18 by agreeing the 12 measures directors actually use.
Analysis and insight
- Modelled the effect of a free delivery threshold on order values, recommending a level that lifted average basket size by 9%.
- Segmented 220,000 gym members by visit pattern, giving the marketing team four groups for a churn-prevention campaign.
- Forecast weekly call volumes in Python for a 300-seat contact centre, keeping rota errors within 5% over the winter peak.
Stakeholders, governance and automation
- Ran requirements workshops with finance and operations before building, halving rework on new dashboard requests.
- Completed data protection impact assessments for two new reports holding personal data, approved by the data protection officer.
- Moved 25 manual Excel reports to scheduled Python scripts stored in Git, freeing a day of analyst time each week.
Action verbs for a data analyst CV
Start each bullet with a precise verb instead of “responsible for”.
- Aggregated
- Analysed
- Automated
- Benchmarked
- Built
- Cleansed
- Consolidated
- Designed
- Documented
- Forecast
- Identified
- Interpreted
- Mapped
- Migrated
- Modelled
- Monitored
- Optimised
- Presented
- Prioritised
- Quantified
- Reconciled
- Segmented
- Standardised
- Streamlined
- Validated
- Visualised
Find more by category with the free action verb finder.
Best CV format for a data analyst
Use a reverse-chronological data analyst CV in a single column: personal profile, technical skills, employment history, then education and qualifications. Graduates, apprentices and juniors fit one side of A4; analysts with five or more years in data usually need two. Leave off a photo, date of birth and full address.
| Your situation | Format | Length | Lead with |
|---|---|---|---|
| Graduate with a data internship | Profile, skills, internship, education, projects | 1 page | Internship results, SQL and Excel, degree and dissertation |
| School leaver or graduate with no data experience | Skills-led: profile, skills, projects, education, part-time work | 1 page | Degree or A-level maths, SQL and Excel, portfolio projects |
| Career changer into data | Hybrid: profile and technical skills before experience | 1 page | Training, data tasks in your current job, sector knowledge |
| Data analyst with 1-4 years in data | Reverse-chronological | 1 page | Tools, data scale and decisions your analysis changed |
| BI analyst with five or more years | Reverse-chronological with a technical skills line | 2 pages | Models, platforms, governance and number of users |
| Experienced NHS or public sector analyst | Reverse-chronological, matched to the person specification | 2 pages | Data sets, reporting systems, band or grade |
| Senior or lead analyst | Reverse-chronological | 2 pages | Team size, budget, priorities and executive impact |
Every example above follows these rules, on A4 and without a photo, date of birth or full address.
How to write a data analyst CV that gets interviews
A data analyst CV gets interviews when every claim is backed by a tool, a data set and a result. Hiring managers skim for SQL, Excel, a visualisation tool and Python or R, then look for proof that your analysis changed a decision.
Give scale and outcomes: records handled, reports automated, hours saved, users served or money affected. ‘Cut month-end reporting from five days to two by automating 15 reports’ beats ‘responsible for reporting’. Name the setting, such as retail, the NHS, housing or financial services, because data sets and keywords differ.
Job titles vary. The National Careers Service lists statistics officer as another title for a data analyst-statistician, and adverts also use MI analyst, insight analyst, information analyst and BI analyst. Use the advert’s title under your name when it fairly describes your experience.
Data analyst CV with no experience
You can write a strong junior or entry level data analyst CV with no experience by leading with skills you can prove: a numerate degree or A-level maths, SQL and Excel, and two or three portfolio projects using real public data, such as ONS or data.gov.uk releases.
In England, the National Careers Service lists apprenticeships from the Software and Data Level 2 Foundation Apprenticeship and Data Technician Level 3 to Data Analyst Level 4 and degree apprenticeships at Levels 6 and 7, plus a T Level in Digital Data Analytics. Other UK nations run their own programmes.
Career changers should mine their current job for data work: reports built, spreadsheets fixed, KPIs tracked. Put sector knowledge up front, because an analyst who understands housing repairs, contact centres or ward flow is valuable. Add certificates such as Google Data Analytics or PL-300 with the year.
How to show technical skills and projects on a data analyst CV
Show technical skills in two places: a short skills line grouped by type (languages, BI tools, databases, cloud), and inside your bullets, where each tool is tied to a result. A list on its own proves little.
List only tools you could use in a technical test. Many data analyst interviews include a SQL or Excel exercise, so write ‘Python (pandas)’ rather than ‘Python’ if that is your real level.
For each project, give the question, data source, method and finding in one line, and link a GitHub or portfolio profile. Never publish personal or confidential employer data; UK GDPR applies to any personal data you process.
Applying for NHS and Civil Service data analyst jobs
NHS data analyst and information analyst posts are advertised on NHS Jobs, Trac or Jobtrain at an Agenda for Change band. Shortlisting scores your application against the person specification, so name the data sets you know, such as ECDS, SUS+ or referral to treatment data.
Civil Service roles are assessed against Success Profiles: behaviours, strengths, ability, experience and technical skills. The advert says which elements apply. Government analysts increasingly build Reproducible Analytical Pipelines in R or Python with Git, so mention version control and peer-reviewed code.
Keywords to include on a data analyst CV
Mirror the exact tools and tasks in the advert, because many UK employers and recruitment agencies screen applications with an ATS, and NHS shortlisters score against the person specification. Work keywords into your skills and bullets naturally rather than pasting a block of terms.
- SQL, T-SQL, PostgreSQL, Snowflake, BigQuery
- Power BI, DAX, Power Query, Tableau, Looker Studio
- Python (pandas, NumPy, scikit-learn), R (tidyverse)
- Excel, pivot tables, XLOOKUP, VBA
- Data cleaning, data quality, ETL, data modelling, star schema
- Dashboards, KPIs, MI reporting, forecasting, A/B testing, regression
- UK GDPR, data protection, information governance, DPIA
- Stakeholder management, requirements gathering, data storytelling
What to include and leave off a UK data analyst CV
| ✓ Include | ✗ Avoid |
|---|---|
| A 3-5 line personal profile naming your tools, sector and target role | A photo, date of birth, age, marital status or nationality |
| A technical skills line grouped by languages, BI tools, databases and cloud | Your full home address or National Insurance number |
| Scale: records, reports, users or budgets you work with | Named referees (leave them off or write ‘References available on request’) |
| Results: hours saved, errors cut, decisions or money influenced | Skill-rating bars or star charts that ATS cannot read |
| Degree with classification, A-level maths and any apprenticeship | Tools you could not use in a technical test |
| Certificates with dates, such as PL-300 or Google Data Analytics | Confidential client names, figures or personal data from employers |
| A GitHub or portfolio link with two or three focused projects | Duty lists such as ‘responsible for reports’ with no outcome |
| Right to work in the UK, if the advert asks for it | Long lists of every tool you have ever opened |
How to write a data analyst CV
- Read the advert and person specification. Highlight the tools, data sets and tasks the employer names, such as ‘SQL Server’, ‘Power BI’ or ‘stakeholder reporting’. These are your keywords, and they show which projects and roles to lead with on your data analyst CV.
- Write a personal profile. In 3-5 lines, give your experience or training, sector, three core tools and the role you want, plus one result. Graduates can lead with their degree and strongest project instead of job history.
- Add a technical skills section. List 8-12 skills grouped by type: query languages, BI and visualisation tools, programming, databases and cloud platforms, and analysis methods. Include only tools you could use confidently in a technical test.
- List your employment history with numbers. Work backwards from your current role. Give recent jobs 4-5 bullets that start with an action verb and include data scale, users or a measurable result. Older or unrelated roles need one or two bullets showing transferable skills.
- Add education, certificates and projects. Give your degree and classification, summarised A-levels or GCSEs, apprenticeships and certificates with dates. Add a projects section with one line per project covering the question, data source, method and finding, plus a GitHub link.
- Proofread, test and save. Check every figure and date, because errors on a data analyst CV undermine your claim to attention to detail. Run it through an ATS checker, save as Word or PDF as the advert asks, and name the file ‘Firstname-Surname-CV’.
Data Analyst salary in the UK
National averages for England. Use them to benchmark offers, not as a promise for any single job.
The National Careers Service puts average pay for a data analyst-statistician at £28,000 a year for new starters, rising to around £65,000 with experience. Typical hours are 37 to 40 a week (between 8am and 6pm).
Source: National Careers Service, Data analyst-statistician job profile (Department for Education), contains public sector information licensed under the Open Government Licence v3.0. Figures are averages; pay varies by region, employer and experience.
Covering letter tip for a data analyst
Open your data analyst covering letter with the job title and one result that matches the advert, such as a report you automated or a decision your analysis changed. Then match two requirements with short examples, name the tools you used and say why the organisation’s data interests you. For NHS posts, write a supporting statement instead.
Start from our cover letter templates or draft one in seconds with the cover letter generator.
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