Biostatistician
You use mathematics and statistics to answer the questions medicine cannot answer alone.
What this life looks like
Is this new treatment better than the old one? Does this vaccine work? Are these two diseases related? Which communities are most at risk from this outbreak? These questions sound clinical, but they are fundamentally mathematical – and answering them properly requires a Biostatistician. As a Biostatistician you design studies, analyse health data, develop statistical models, and interpret findings in ways that are rigorous, reproducible, and clinically meaningful. You are the person who ensures that the conclusions drawn from research are valid – that the sample was large enough, that the analysis was appropriate, that the results were not produced by chance. Without biostatisticians, clinical research produces misleading results, public health programmes target the wrong populations, and health policy is built on shaky evidence. In Africa, where health research is expanding rapidly, the demand for biostatisticians who understand both the statistical methods and the health context is growing fast. This is a career for people who love mathematics and want to apply it to some of the most important questions in human health.
What she actually does
A Biostatistician designs the statistical components of research studies, calculates sample sizes, develops analysis plans, cleans and manages research datasets, applies statistical methods including regression, survival analysis, and multilevel modelling, interprets results and contributes to research publications, develops statistical models for disease surveillance and health system monitoring, and advises researchers on appropriate analytical approaches for their study questions.
Where you can work
| Sector | Places in Africa |
|---|---|
| Academic research institutions and universities | University of the Witwatersrand (South Africa), Makerere University (Uganda), University of Ibadan (Nigeria), Stellenbosch University |
| Public health research organisations | African Population and Health Research Center (APHRC) (Kenya), Nigerian Institute of Medical Research (NIMR), Medical Research Council (MRC) Gambia |
| International health organisations | WHO AFRO, Africa CDC, and UNAIDS |
| Clinical trials units | Infectious Diseases Institute (IDI) (Uganda), CAPRISA (South Africa), KEMRI-Wellcome Trust (Kenya) |
| Government health data and surveillance agencies | Nigeria Centre for Disease Control (NCDC), National Institute for Communicable Diseases (NICD) (South Africa), Ethiopian Public Health Institute (EPHI) |
| Pharmaceutical companies conducting clinical trials | Aspen Pharmacare (South Africa), 54gene (Genomics/Clinical research in Nigeria), Sanofi Africa |
Why it matters in Africa
Africa generates enormous amounts of health data – from disease surveillance systems, demographic surveys, clinical trials, and electronic health records – but has too few biostatisticians to analyse it well. Poorly analysed data produces misleading results that can misdirect health policy and programme investment. Africa needs biostatisticians who understand both the technical statistical methods and the specific challenges of analysing health data from African populations and health systems.
Your pathway in
Mathematics and Statistics are essential at secondary school – this career begins with a love of and skill in quantitative thinking. You then complete a Bachelor of Science in Statistics, Mathematics, or Biostatistics. A postgraduate degree in Biostatistics or Epidemiology is typically required for senior research roles and is available at institutions including the University of Cape Town, the African Institute for Mathematical Sciences, Makerere University, and the University of Ghana.
Skills you will need
Technical: Statistical theory including probability, regression, survival analysis, and Bayesian methods, proficiency with statistical software especially R and SAS, study design, data management, and scientific writing. Human: The ability to communicate statistical findings clearly to clinicians and policymakers who may not be statistically trained, patience in explaining methods, meticulous precision in analysis, and the intellectual rigour to acknowledge uncertainty. Digital tools: R, SAS, Stata, SPSS, Python for data analysis, REDCap for research data management, and data visualisation tools.
A woman in this field
Dr. Theresa Munyombwe
Zimbabwe / South Africa
Dr. Munyombwe is a senior Biostatistician and academic at the University of the Witwatersrand. She is a key member of the Sub-Saharan Africa Consortium for Advanced Biostatistics (SSACAB). Her work focuses on structural equation modeling and longitudinal data analysis, particularly in the context of HIV and maternal health. She is a passionate advocate for mentoring the next generation of African female statisticians, ensuring they have the technical skills to lead high-impact clinical research across the continent.
Take your first step
Mathematics is your most important subject at school – if you enjoy it and are good at it, biostatistics offers a way to apply that skill to meaningful health questions. Statistics is even more directly relevant if it is offered at your school. Look up the African Institute for Mathematical Sciences, which trains postgraduate students in mathematical sciences across Africa and has an inspiring community of African mathematicians. Read about the role of statistics in some of the great public health discoveries – from John Snow's mapping of the Broad Street cholera outbreak to the statistical proof that smoking causes cancer. Statistics, done well, changes the world.