Monitoring Evaluation Research Learning (MERL ) Associate

• An honours degree in economics, public health, biology, epidemiology, statistics, psychology, computer science, or in any other quantitative social science field
• Strong statistical, analytic, quantitative and qualitative data interpretation skills
• Moderate to strong exposure to econometric, impact evaluation or other causal inference techniques
• The ability to manipulate large, complex data sets into manageable, understandable reports
• Experience and confidence in conducting literature reviews spanning a range of research fields
• Strong skills in Stata (preferred), R, SPSS, or Python
• Interest in data visualisation

• Conducting literature reviews detailing barriers to health for disadvantaged citizens in multiple African countries within specific health domains and their intersections
• Identifying evidence-based interventions addressing barriers from public health, behavioural science, development economics, and other research fields
• Identifying innovative and evidence-based instruments for measuring behavioural, clinical, and psychological outcomes including the identification and operationalisation of health impact indicators within the organisation's MERL framework
• Design surveys and other digital data-gathering methods to assist programme evaluation methods
• Design and implement qualitative data collection activities to support programme evaluation and learning, and when necessary, manage qualitative data collection firms for larger scale efforts
• Using quantitative statistical programmes and methods to clean and interpret data generated within the organization’s mobile platform or other interventions

• Python
• R
• Reporting
• SPSS
• Stata
• Statistical Analysis