Free Mid-level statistician CV (2026)

Start with a clear CV headline that includes your job title and a primary skill or domain, for example "Mid-Level Statistician, Clinical Trials and R Programming". Write a 2-3 sentence professional summary that highlights years of experience, the datasets you have worked with (e.g. clinical trial data, real-world evidence), and a measurable outcome such as improved model accuracy or reduced processing time.\n\nIn your summary use active language and name the tools you use most, like R, Python, SQL, or Bayesian methods.

Avoid vague claims and instead show what you did and the value you delivered, for example "built a predictive model that improved forecasting accuracy by 12 per cent" when you have a verified number to cite. If applying to NHS or public sector roles, mention relevant healthcare data work, DBS clearance where applicable, and your right-to-work status in the UK.

List roles in reverse chronological order and keep each job entry to 3-5 bullet lines that combine context, action, and outcome. For each role include the employer name, location, job title, dates in DD/MM/YYYY format, and a short context line that states the team size and main focus, such as exploratory analysis for product metrics or designing clinical endpoints.\n\nFor each bullet start with a strong verb, name the method or tool, and quantify the result when you can.

Examples include "Designed survival analysis pipeline in R to evaluate treatment effects, reducing analysis time from two weeks to five days" and "Developed A/B test analytics framework using SQL and Python to monitor feature impact across 200k daily users."

Organise skills into small groups like Programming, Modelling, and Data Tools so recruiters can scan easily. Include specific libraries and frameworks such as tidyverse, scikit-learn, Stan, or PyMC, and mention data platforms such as Redshift or BigQuery when relevant to your experience.\n\nAvoid long generic skill lists that do not reflect your depth in each area.

Instead include 6 to 10 targeted skills and for two or three of them mention how you applied them in your work experience section to show practical competence.

Include 2-3 standout projects that show end-to-end work from data acquisition to presentation of results. For each project give the objective, your role, the methods used (e.g. survival analysis, Bayesian modelling, time-series forecasting), and the outcome, and add a link to a GitHub notebook or a portfolio if you can share non-sensitive code or visualisations.

Where possible, relate results to business or healthcare outcomes and mention any NHS or public sector impact.

Format for the UK audience: use A4 paper, typically two pages, with a clean, professional font (Arial, Calibri or similar) and bullet-point structure. Put contact details and LinkedIn at the top, followed by a concise summary, then work experience, education, and skills.

Include education details using UK terms (GCSEs, A-levels, UCAS, Russell Group universities). If relevant to healthcare roles, reference NHS pay bands where appropriate and your eligibility to work in the UK.

Mention any right-to-work status and DBS clearance if required. Do not include a photo; tailor content to the job spec and provide links to non-sensitive reports or dashboards.