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.

Key Responsibilities:

• Lead the design and execution of all primary quantitative analyses, impact evaluation, and effective coverage estimation.
• Specify detailed statistical analysis plans.
• Develop, maintain, and govern harmonised, reproducible analytic codebases (R, Stata, Python), ensuring compatibility with federated data execution and secure in-country runs.
• Oversee data preparation for all analyses, including variable construction, temporal alignment, cohort definition, and linkage across routine and evaluation datasets.
• Implement and supervise advanced data quality assurance and reproducibility processes.
• Lead the Year 1 mortality recalibration analysis, comparing modelled projections with observed empirical data and updating lives-saved estimates.
• Co-lead statistical quality control processes across countries, ensuring consistency of model implementation, outputs, and reporting.
• Mentor quantitative analysts and work closely with the Senior Data Management RO to align analytic needs with data pipelines and governance requirements.
• Produce high-quality statistical outputs, including technical appendices, codebooks, metadata, and fully reproducible analytic notebooks to support reporting, peer-reviewed publications, and external review.

Vacancy Requirements:

• PhD in Biostatistics/Statistics/Data Science (or equivalent) Mandatory
• At least 5 years post-doctoral research experience. Mandatory
• Demonstrated expertise in ITS, causal inference in observational settings, multilevel models, and routine health data. Mandatory
• Advanced R/Stata/Python; reproducible research; version control; clear technical writing Mandatory

• Lead the design and execution of all primary quantitative analyses, impact evaluation, and effective coverage estimation.
• Specify detailed statistical analysis plans.
• Develop, maintain, and govern harmonised, reproducible analytic codebases (R, Stata, Python), ensuring compatibility with federated data execution and secure in-country runs.
• Oversee data preparation for all analyses, including variable construction, temporal alignment, cohort definition, and linkage across routine and evaluation datasets.
• Implement and supervise advanced data quality assurance and reproducibility processes.
• Lead the Year 1 mortality recalibration analysis, comparing modelled projections with observed empirical data and updating lives-saved estimates.
• Co-lead statistical quality control processes across countries, ensuring consistency of model implementation, outputs, and reporting.
• Mentor quantitative analysts and work closely with the Senior Data Management RO to align analytic needs with data pipelines and governance requirements.
• Produce high-quality statistical outputs, including technical appendices, codebooks, metadata, and fully reproducible analytic notebooks to support reporting, peer-reviewed publications, and external review.

• Advanced R/Stata/Python
• Reproducible research
• Version control
• Clear technical writing
• ITS
• Causal inference in observational settings
• Multilevel models
• Routine health data

• PhD in Biostatistics/Statistics/Data Science (or equivalent)
• At least 5 years post-doctoral research experience.