Data Analyst at Kenya Medical Research - KEMRI

Position Summary

In collaboration with KEMRI-WASH U investigators, the Data Analyst will guide the analysis activities for the A4A study and have authorship opportunities on projects applying challenging statistical methods. As the Data Analyst, the incumbent will lead planning, designing and implementation of research projects, as well as analysis and interpretation of statistical data. He/she provides advice on implications of results for program planning and decision making. The Data Analyst will provide mentorship and management support to the Statistician.

Duties and Responsibilities:

•  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 A4A 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

Key Qualifications:

•  Bachelor’s Degree in Biostatistics/Statistics or Applied Mathematics as evidenced by possession of at least a Degree from a recognized University
•  Advance level knowledge of statistical software: SAS and/or STATA data management is required
•  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