Master’s degree in Econometrics, Statistics, Data Science, Public Health, Economics, or a related field.

Past experience in managing an evaluation process from design to reporting in a development or research context.

Experience writing code for data cleaning and analysis (R, Python, Stata).

Experience designing and managing quantitative surveys using SurveyCTO or Open Data Kit.

Past experience managing research teams or enumerators in the field

Rigorous Evaluation Design: contribute to our learning agenda by designing sampling strategies and protocols for upcoming process evaluations, ensuring our methods are robust enough to capture nuanced data.

End-to-End Research Management: lead the execution of internal and external evaluations. This includes managing pools of enumerators, securing ethical clearance, overseeing data collection quality, and ensuring strict adherence to study protocols in the field.

Advanced Statistical Analysis: Lead the statistical analysis for complex studies, including Difference-in-Difference (DiD) models and longitudinal tracking. You will write the R scripts to match client IDs across historical datasets to track continuation rates.

Data Architecture & Engineering: contribute to building automated data workflows. Using R, Python, or SQL, you will engineer data systems that automatically clean incoming streams and feed into dashboards that level up our reporting.

Federal Stakeholder Representation: Represent the Lafiya MEL department in meetings with Federal-level stakeholders and technical partners, presenting our evidence to align with national health priorities.

Publication Ready Evidence: produce analysis of sufficient rigour for academic publication and high-level donor reporting (e.g., Gates Foundation).

Strategic Communication: Translate complex statistical findings into clear, defensible evidence that can be used to influence national health policy and program strategy