Associate Data Science

About the role

The Associate, Data Science will work with Rwanda's Ministry of Health and CHAI to improve the quality, governance, and use of health data for policy decision‑making. Reporting to the head of data science at the National Health Intelligence Centre and to CHAI’s digital health program manager, the role bridges raw health data, AI models, and real‑world decisions.

Key responsibilities

• Lead advanced descriptive, predictive, and inferential analyses across clinical, surveillance, and health‑systems datasets.
• Develop and validate predictive models, risk‑stratification algorithms, and forecasting tools.
• Design feature‑engineering pipelines from EMRs, HMIS, LMIS and surveillance platforms.
• Support AI engineers with high‑quality training datasets, bias detection and data representativeness testing.
• Implement data‑quality frameworks, conduct audits, outlier detection and ensure compliance with national data‑governance standards.
• Build decision‑support dashboards and translate analytical outputs into policy briefs and executive reports.
• Collaborate with data engineers to optimise pipelines, ensure reproducibility and production readiness.
• Mentor junior data scientists, lead analytics communities of practice and review research designs.

Required profile

• M.Sc. degree in Data Science, Applied Mathematics, Statistics, Epidemiology, Health Informatics or related field.
• 5–8 years of professional experience in data analytics, statistical modelling and machine learning, preferably in health or public‑sector contexts.

Required skills

• Advanced statistical modelling and hypothesis‑testing techniques.
• Machine‑learning model development for tabular health data and time‑series forecasting.
• Feature engineering and data‑pipeline construction.
• Data quality assessment, governance and metadata management.
• Creation of public‑health dashboards and decision‑support tools.
• Collaboration with data engineers and AI engineers for scalable solutions.