Statistician

CAPRISA is an award-winning global research organisation located on the campus of the Nelson Mandela School of Medicine in Durban, South Africa and undertakes research in HIV and TB at four clinical research sites in KwaZulu-Natal.  

CAPRISA’s goal is to undertake globally relevant and locally responsive research that contributes to understanding HIV Vaccines and Pathogenesis, Prevention and Epidemiology, the links between Tuberculosis and AIDS treatment. CAPRISA is a UNAIDS Collaborating Centre for HIV Research and Policy and is recognised as a DSI-NRF Centre of Excellence in HIV Prevention and hosts the SAMRC HIV-TB Pathogenesis and Treatment Research Unit. 

CAPRISA seeks to appoint a Statistician who will be responsible for providing statistical support and methodological advice for studies conducted at CAPRISA.  The incumbent will also be responsible for statistical analysis of studies, writing up of results as well as providing monthly reports on studies. The successful incumbent will join the CAPRISA Statistics team based at our Doris Duke Medical Research Institute offices (DDMRI) in Durban.

Site

•    Provide statistical advice for the design of clinical trials and different types of observational studies and contribute to protocols and grant applications
•    The ability to undertake projects in Biostatistical methodology and applied Biostatistical research; or being a co-investigator or study statistician in health-related project
•    Determine and undertake appropriate analysis of clinical trials, observational studies and de-identified routine health records data and record statistical analysis code in a reproducible format.
•    Write-up study design, sample size, statistical analysis plans and study analysis results
•    Prepare routine and adhoc study reports and contribute to presentations and publications

•    Master’s degree or higher in Statistics, Biostatistics or a related quantitative discipline. A PhD in Statistics or a related field will be advantageous   (with undergraduate in a related quantitative discipline) 4 years of research and statistical analysis experience
•    Strong experience in R and/or Python; experience with SAS, Stata or other statistical software will be advantageous 
•    Experience in applied statistical research, epidemiological studies and analysis of health-related data
•    Basic knowledge of clinical and microbiome research and epidemiology
•    High level of computer literacy in MS office (Word, Advanced Excel and Outlook)
•    Experience with longitudinal data, repeated measurements, survival/time-to-event analysis and multivariable statistical modelling will be advantageous 

•    Strong analytical, statistical and problem-solving skills with excellent attention to detail 
•    Able to work under pressure in a changing environment
•    Ability to work independently and fit in well within a multi-disciplinary team
•    Ability to communicate statistical concepts to non-statisticians
•    Managing time and work/deadline driven
•    Excellent written, verbal communication skills and interpersonal skills