Biostatistician
SOC 15-2041.01 · ESCO 2120 · OSCA 223132
Role snapshot
Overview
Designs clinical trials and epidemiological studies, then analyses the resulting health data using advanced statistical methods. Builds predictive models, interprets complex results for medical researchers, and ensures study conclusions are statistically sound. Applies statistical expertise to biological and health-related problems, contributing to evidence-based decision-making in healthcare and public health.
Provides crucial statistical evidence to validate new treatments, understand disease patterns, and improve public health outcomes, directly influencing medical research and patient care.
On the job
- Develop statistical analysis plans for clinical trials and observational studies.
- Perform complex statistical modeling and data analysis using specialized software.
- Interpret and present statistical findings to non-statistical audiences, such as medical doctors and researchers.
- Collaborate with interdisciplinary teams to design research studies and experiments.
- Ensure the integrity and validity of research data and statistical conclusions.
Tools & technology
Average salary
Job outlook
GrowingJob growth is expected to be above average over the next five years.
Education & training
Advanced degree (Master's or PhD) in Biostatistics, Statistics, Mathematics, or a related quantitative field with a focus on biological or health sciences.
AI impact outlook
Note — this is our current view. AI is moving fast, so we revisit these ratings.
Show how this was assessed Hide the detail
Note — this is our current view. AI is moving fast, so we revisit these ratings.
Show how this was assessed Hide the detailWhy this role received this rating
Core task exposure
moderate
How much of the role’s important work could AI perform?
AI can assist with statistical modeling, data analysis, and pattern identification, but the design of novel studies remains human.
End-to-end automation
low
Can AI complete the work without substantial human involvement?
The ethical implications, regulatory scrutiny, and necessity of human judgment in study design and interpretation prevent full automation.
Adoption pressure
moderate
How likely are employers to introduce AI into this work?
The regulated nature of healthcare slows full automation, but efficiency drives adoption of AI for data analysis within clinical trials.
Human dependence
strong
How much does success depend on human judgement, relationships and accountability?
Success critically depends on ethical responsibility, nuanced interpretation of health data, communication with medical teams, and accountability for study conclusions.
Protective — a higher rating lowers the overall score.
Role adaptability
strong
How easily can the role evolve as AI takes on more tasks?
The role requires continuous adaptation to new statistical methods, computational tools, data sources, and evolving regulatory standards in health research.
Shown for context — not part of the score.
What AI may take on
These are the parts of the role most likely to be automated or significantly accelerated.
- Automating routine statistical calculations and data summaries
- Suggesting appropriate statistical models for given datasets
- Performing power calculations for study design optimization
- Generating standard statistical reports and visualizations
- Identifying hidden patterns and correlations in large health datasets
Where people remain essential
These parts continue to depend heavily on human judgement, relationships and accountability.
- Developing novel statistical analysis plans for complex trials
- Designing innovative epidemiological and clinical studies
- Interpreting nuanced statistical findings for clinical significance
- Collaborating with medical researchers on study design and implications
- Ensuring regulatory compliance and ethical conduct of research
- Communicating complex statistical concepts to non-experts
- Bearing accountability for the integrity of study conclusions
How the role may evolve
From manual analysis to AI-augmented study design and complex interpretation.
The role will evolve from manual statistical execution to leveraging AI for routine tasks, freeing biostatisticians to focus on innovative study design and the critical, contextual interpretation of complex health data. This demands deeper scientific and ethical reasoning.
Strengthen your future fit
- Advanced causal inference and experimental design expertise
- Proficiency in AI/ML methods for health data analysis
- Exceptional communication for interdisciplinary teams
- Deep understanding of clinical research regulations and ethics
- Ability to critically evaluate automated statistical insights
- Assessment horizon
- 3–7 years
- Confidence
- High
- Last reviewed
- August 2026
- Methodology
- v1.0
This assessment reflects current AI capabilities and expected adoption patterns. Actual impacts will vary by industry, employer and the way each role is performed.
Career pathways
WHERE YOU COULD GO
CURRENT ROLE
Biostatistician
Data & AI
ADJACENT MOVES
STARTING POINTS
Who thrives here
Interest profile
investigative · ICS
People who enjoy rigorous investigation of data, applying structured analytical methods, and collaborating to share scientific insights thrive in this role.
Personality characteristics
Analytical Thinker
Enjoys dissecting complex problems and applying logical, data-driven approaches to find solutions.
Methodical & Precise
Dedicated to accuracy and rigor in statistical analysis, ensuring data integrity and reliable conclusions.
Collaborative Communicator
Effectively shares complex statistical concepts and findings with non-technical medical and research teams.
Calm Under Pressure
Maintains composure when facing tight deadlines, conflicting data, or critical feedback on research findings.
Structured Approach
Prefers working within established frameworks and protocols to ensure consistency and reproducibility in research.
Best for
- Individuals passionate about applying advanced statistics to solve real-world health challenges.
- Those who thrive on meticulous data analysis and enjoy translating complex numbers into clear scientific narratives.
- Professionals seeking a career that directly contributes to medical knowledge and public health.
Watch out for
- Requires advanced quantitative skills and continuous learning in statistical methods.
- Can involve long periods of independent data analysis and detailed report writing.
- Results may not always be what researchers hoped for, requiring objective communication of findings.
A week in the life
A representative working week for a Biostatistician — where the deep work, meetings, and admin actually land.
Real people. Real results.
Thousands of people
can't be wrong.
Frequently asked questions about Biostatistician roles
What does a Biostatistician do?
A Biostatistician designs clinical trials and epidemiological studies, then analyses the resulting health data using advanced statistical methods. Builds predictive models, interprets complex results for medical researchers, and ensures study conclusions are statistically sound. Applies statistical expertise to biological and health-related problems, contributing to evidence-based decision-making in healthcare and public health. Provides crucial statistical evidence to validate new treatments, understand disease patterns, and improve public health outcomes, directly influencing medical research and patient care.
How much does a Biostatistician earn?
A Biostatistician earns a median of $110,000 per year in the US, typically ranging from $80,000 to $150,000.
What qualifications do you need to become a Biostatistician?
To become a Biostatistician, advanced degree (Master's or PhD) in Biostatistics, Statistics, Mathematics, or a related quantitative field with a focus on biological or health sciences.
What personality suits a Biostatistician?
Biostatistician roles tend to suit people who are highly conscientious — precise, organised and strong on follow-through (Conscientiousness 88/100) and open and curious — drawn to variety, ideas and new approaches (Openness 75/100). The traits that matter most in the role are Analytical Thinker, Methodical & Precise, Collaborative Communicator and Calm Under Pressure. Enjoys dissecting complex problems and applying logical, data-driven approaches to find solutions. On interests, Biostatistician maps to an ICS Holland Code profile — people who enjoy rigorous investigation of data, applying structured analytical methods, and collaborating to share scientific insights thrive in this role.
Who does a Biostatistician role suit?
A Biostatistician role is usually a strong fit for these reasons. High Investigative and Conventional alignment: the role demands rigorous analytical thinking and adherence to structured methodologies. Significant deep work blocks allow for focused statistical modeling and research. Opportunities for collaborative communication with interdisciplinary teams, aligning with Social interests.
What are the downsides of being a Biostatistician?
Biostatistician roles come with trade-offs worth weighing up. Requires advanced quantitative skills and continuous learning in statistical methods. Can involve long periods of independent data analysis and detailed report writing. Results may not always be what researchers hoped for, requiring objective communication of findings.
What is the work environment like for a Biostatistician?
Work as a Biostatistician is mostly office-based with hybrid arrangements common, semi-structured — a mix of set processes and self-directed work, a moderate pace and high exposure to clients or stakeholders. Around 80% of the week is focused deep work.
What skills do you need to be a Biostatistician?
Core skills for a Biostatistician include Statistical modeling, Data interpretation, Clinical trial design, Epidemiological methods, Data visualization and Scientific communication.
How do you become a Biostatistician?
Common entry routes into Biostatistician roles include Statistical Analyst, Research Assistant Statistics and Junior Data Analyst.
What career progression is there for a Biostatistician?
From a Biostatistician role, common next steps include Senior Biostatistician and Principal Biostatistician; lateral moves include Data Scientist (Health/Bioinformatics) and Quantitative Research Scientist.
What is the job outlook for Biostatistician roles?
The outlook for Biostatistician roles is currently rated growing. Job growth is expected to be above average over the next five years.
Will AI replace Biostatistician roles?
Traitstack rates automation risk for Biostatistician roles at 42 out of 100, which is moderate. Statistical modeling and routine analysis are increasingly AI-assisted; however, designing novel trials, nuanced interpretation, and accountability for clinical conclusions are human tasks. AI is most likely to take on automating routine statistical calculations and data summaries, suggesting appropriate statistical models for given datasets and performing power calculations for study design optimization. Developing novel statistical analysis plans for complex trials, designing innovative epidemiological and clinical studies and interpreting nuanced statistical findings for clinical significance stay with people. From manual analysis to AI-augmented study design and complex interpretation. That score measures how much of the work could change, not the likelihood the job disappears. It is Traitstack's current view, revisited as AI capability moves.