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CV Template · Statistician
Statistician CV template.
A strong statistician CV should show how you turn complex data into defensible conclusions. Employers want evidence of sound methodology, reproducible workflows, and the ability to communicate findings to technical and non-technical teams.
Writing a strong Statistician CV
Hiring managers reviewing statistician CVs look closely at your statistical methods, software stack, and experience with real datasets. Include tools such as R, Python, SAS, Stata, SQL, SPSS, or MATLAB, and name the models or techniques you use, such as regression, survival analysis, Bayesian inference, time-series forecasting, mixed-effects models, or experimental design. For clinical, academic, government, or finance roles, mention deliverables like statistical analysis plans, validation reports, dashboards, peer-reviewed publications, regulatory submissions, or reproducible code repositories. If relevant, add degrees, certifications, domain specialisms, and experience with data governance or IRB-approved studies.
Three things that matter most
- Name the statistical methods behind your work, not just the project topic. For example, specify whether you used logistic regression, Cox proportional hazards models, hierarchical modelling, A/B testing, or Monte Carlo simulation.
- Show the full workflow from data cleaning to final deliverable. Mention tools such as R Markdown, Quarto, Jupyter, Git, SQL, SAS macros, or validated analysis datasets if they were part of your process.
- Adapt your CV to the sector you are targeting. A clinical statistician CV should reference SAPs, CDISC, SDTM, ADaM, and regulatory reporting, while a finance or tech CV may prioritise forecasting, experimentation, risk models, and production analytics.
Skills hiring managers look for
Frequently asked
How do I write a statistician CV with no industry experience?
Use academic projects, thesis work, internships, research assistant roles, or competition datasets to demonstrate statistical judgement. Describe the dataset size, methods used, software, assumptions checked, and final output, such as a report, poster, dashboard, or reproducible notebook. If you have a portfolio on GitHub or a personal site, include selected projects that show clean code and clear interpretation.
Which software should I include on a statistician CV?
List the tools you can use in a professional workflow, not every package you have tried once. R, Python, SAS, SQL, Stata, SPSS, MATLAB, Git, and data visualisation tools are common, but the best choices depend on the role. Clinical and pharmaceutical employers often value SAS, CDISC, SDTM, and ADaM, while tech and finance teams may prefer Python, R, SQL, and cloud-based analytics environments.
Should a statistician CV include publications and research papers?
Yes, if they support the role you are applying for. Include peer-reviewed publications, conference abstracts, posters, preprints, or technical reports when they show relevant methodology or domain knowledge. For non-academic roles, keep the list selective and prioritise papers where you contributed to study design, modelling, analysis, or interpretation.
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