Biostatistician Resume: Free Example (2026)

This example emphasizes measurable outcomes and reproducible methods, which matter in biostatistics roles.
You should prioritize projects and results that show your statistical thinking, such as effect sizes, confidence intervals, model performance metrics, or reduced error rates.

Hiring managers and PIs look for evidence you can turn data into interpretable findings, so make results concrete and quantifiable.
The layout is simple and scannable, with a strong header, a short professional summary, a focused experience section, and a skills block.

You should make the top of your resume count, since many reviewers form an impression in 6 to 10 seconds.
Clear labels and consistent formatting help reviewers find your key contributions quickly.

Use a clean, single-column layout with consistent margins and fonts to keep attention on content rather than design.
You should use 10 to 12 point font for body text and slightly larger for headings, and leave white space to separate sections for easier scanning.

Save the file as PDF unless the job posting explicitly requests another format, because PDF preserves layout across devices.
Organize sections in this order, unless you have a reason to change it: contact and title, summary, skills, experience, education, selected projects and publications, and relevant certifications.

You should keep your resume to one page if you have less than 10 years of experience, and to two pages if you have extensive publications or leadership in trials.
Bullet points should be short and start with strong action verbs while focusing on contributions and outcomes.

Write a short title line that states your role and specialization, for example Senior Biostatistician, Clinical Trials or Biostatistician, Genomics.
You should follow the title with a two to three sentence professional summary that highlights your domain, years of experience, and most relevant strengths, such as statistical modeling, trial design, or regulatory submissions.

Keep the summary focused on the job you want, and avoid vague statements without supporting details.
Example summary you can adapt, with specific metrics: Biostatistician with six years of experience designing and analyzing randomized clinical trials, experienced with SAS and R, and led analysis plans for three Phase II trials that supported regulatory submissions.

You should replace the example metrics with your own validated numbers and role descriptions.
Use keywords from the job posting in this section to help pass applicant tracking systems.

Structure each role entry with employer, location, dates, and your job title, followed by 3 to 6 bullet points describing your achievements.
You should lead each bullet with an action verb, then describe the task, the method or tool used, and the measurable outcome when possible.

For example, state the sample size, model type, improvement in prediction accuracy, or reduction in processing time to make the impact clear.
Sample bullet you can adapt: Designed and implemented mixed effects models in R for a multi-center trial of 1,200 participants, which identified a significant treatment by subgroup interaction and informed stratified analysis plans.

You should quantify your contributions, and when you cannot share proprietary numbers, describe the type of result such as improved model fit or validated reproducibility.
When listing tools, avoid long passive lists of software; mention the tool in the context of a result, for example, performed survival analysis in SAS to estimate median progression-free survival.

Group skills into categories such as Statistical Methods, Programming and Data Management, and Domain Knowledge to make it easy for reviewers to scan.
You should include both statistical techniques like generalized linear models and survival analysis, and software such as R, SAS, Python, or SQL, with version or package names when relevant.

For applied areas, add domain terms like clinical trial design, epidemiology, or genomics to show job fit.
Avoid long uncontextualized skill lists that look like keyword stuffing, and instead highlight tools in bullets within the experience or project descriptions.

You should show how a tool was used, for example, automated data cleaning with Python scripts to reduce preprocessing time by X percent, or created reproducible RMarkdown reports for stakeholders.

List your highest degree first, including institution, degree type, and graduation year, and include thesis topic when it directly relates to the role.
You should place relevant certifications such as SAS Base or Clinical Data Management certificates after education.

For publications, include selected peer reviewed articles, conference abstracts, or technical reports that demonstrate your research output and scholarly impact.
When you have many publications, include a short curated list of three to five most relevant works on the resume and link to a full list on a CV or Google Scholar profile.

You should add DOIs or brief citation details so reviewers can verify the work if needed, and be prepared to discuss methods and findings in interviews.

Include one or two short project entries that show end to end work, from design to analysis to communication of results.
You should describe your role, the methods used, and the outcome, for example, implemented a reproducible pipeline in R for data cleaning, analysis, and visualization that cut analysis time and improved handoffs to the results team.

Emphasize collaboration with clinicians, data managers, and regulators when applicable to show you work well in cross functional teams.
If you maintain code repositories or reproducible workflows, state that and provide links if the employer allows external access.

You should avoid sharing proprietary data, and instead describe methods, metrics, and the public tools or packages you used to achieve reproducibility.

Read the job description carefully and mirror the specific statistical methods and domain terms it lists, while keeping wording natural and truthful.
You should place exact phrases such as 'survival analysis', 'mixed effects model', or 'clinical trial statistical analysis plan' where they accurately describe your experience.

Avoid copying the job posting word for word if it makes your sentences awkward, and do not include skills you cannot demonstrate in an interview.
Use section headings that common ATS parse well, such as Experience, Education, and Skills, and avoid headers with unusual characters.

You should test keyword coverage by saving the job description and highlighting overlaps to ensure critical terms appear in both the summary and experience bullets.

Use bullet points of one to two lines per achievement to keep rhythm and readability, and keep verbs in the past tense for completed roles.
You should align dates and locations in a consistent column so reviewers can scan timelines quickly.

If you include figures such as sample sizes or percent changes, keep them concise and consistent in format, for example use numerals like 1,200 or 35% to stand out.
For a template approach, pick a neutral, professional font such as Arial or Calibri and maintain consistent spacing between headings, bullets, and sections.

You should prioritize clarity over novelty, because hiring committees value content that is easy to evaluate.