Kenya Medical Research Institute (KEMRI) is a State Corporation established through the Science and Technology (Amendment) Act of 1979, which has since been amended to Science, Technology and Innovation Act 2013. The 1979 Act established KEMRI as a National body responsible for carrying out health research in Kenya.
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Develop rigorous analysis strategies for abstracts, manuscripts, and program evaluation activities. Authorship as part of these analysis activities.
Apply complex statistical techniques and methods in the processing and analysis of data
Directly supervise and mentor the Statistician
Develop and implement program tracking databases in support of program evaluation activities
Organize and direct the study design, data collection, processing, analysis and publication of statistical data on various subject matter relevant to the YIA Oncology study
Support investigators to operationalize research goals, refine statistical hypotheses, develop statistical analysis plans and explain statistical implications of results.
Merge data across databases and check for data inconsistencies and outliers using STATA
Clean and edit complex medical record data for analysis
Generate data reports on program activities, both routine and as requested
Document methodologies and procedures used in the compilation and analysis of data, as well as data sources and limitations of estimates and guidelines for their use
Provide advice on sample size calculation
Provide advice on the statistical interpretation and implications of results for program planning and decision-making
Prepare tables, figures, results, and statistical methods narratives for abstracts and publications
Vacancy Requirements:
Strong academic qualifications in Biostatistics/Statistics or Applied Mathematics as evidenced by possession of at least a Degree from a recognized University
At least 4 years’ experience in statistical work at the professional level, preferably in a healthcare setting
Advance level knowledge of statistical software: SAS and/or STATA data management is required
In-depth, comprehensive, and evolving knowledge of statistical and mathematical analysis techniques integrated with computer applications
Demonstrated expertise in the following techniques is required: logistic and linear regression, mixed model, longitudinal data analyses, interrupted time series analyses, factor analyses, complex survey sample analyses, survival analyses, missing imputation, bootstrapping
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