About the Health System Strengthening Programme in Rwanda
The Government of Rwanda aims to achieve Universal Health Coverage (UHC) by improving equitable access to quality health services, as outlined in the Fourth Health Sector Strategic Plan (HSSP IV).
CHAI Rwanda’s Health System Strengthening programme works closely with government institutions, including the Ministry of Health and the Rwanda Social Security Board (RSSB).
The programme supports initiatives intended to improve primary health care, strengthen health financing, increase health workforce availability, and promote the sustainable delivery of essential health services.
Within this programme, the Associate, Data Science will contribute to the use of reliable health data and advanced analytics to support national health priorities.
Job Purpose
The Associate, Data Science will work with the Ministry of Health and report directly to the Head of Data Science at the National Health Intelligence Centre. The role will also involve reporting to CHAI’s Health System Strengthening Digital Health Programme Manager for specific CHAI-supported initiatives.
The successful candidate will lead advanced data analytics, statistical modelling, and applied machine learning across priority public health and clinical areas.
The position focuses on transforming raw health data into reliable, explainable, and actionable information that supports artificial intelligence development, policy decisions, and health system performance improvement.
The role also requires scientific rigour, reproducible analytical methods, strong data governance, and the ability to translate complex findings into practical recommendations.
Key Responsibilities
1. Advanced Data Analytics and Statistical Modelling
The Associate will:
- Lead descriptive, predictive, and inferential analyses using clinical, disease surveillance, and health systems datasets.
- Develop and validate predictive models, risk-stratification algorithms, forecasting models, and epidemiological analyses.
- Apply statistical methods, hypothesis testing, and causal inference to support decision-making.
- Ensure analytical findings are scientifically defensible, clinically interpretable, and relevant to public policy.
2. Feature Engineering and Machine Learning Support
Responsibilities include:
- Design feature engineering pipelines using data from Electronic Medical Records (EMRs), Health Management Information Systems (HMIS), Logistics Management Information Systems (LMIS), and surveillance platforms.
- Support AI engineers by preparing high-quality training datasets.
- Conduct feature selection, bias detection, and data representativeness testing.
- Contribute to machine learning development, particularly for structured health data, time-series forecasting, and population-level risk prediction.
3. Data Quality, Governance, and Integrity
The successful candidate will:
- Develop and implement data quality frameworks covering completeness, consistency, accuracy, and timeliness.
- Conduct data audits and analyse outliers, bias, and missing data.
- Ensure compliance with national health data governance standards, privacy requirements, and ethical data-use policies.
- Maintain data documentation, metadata standards, and data lineage records.
4. Health Systems Intelligence and Decision Support
Key duties include:
- Develop analytical decision-support tools and public health dashboards.
- Support disease burden monitoring, resource allocation, and service delivery optimization.
- Translate analytical findings into policy briefs, executive dashboards, and technical reports.
- Ensure that outputs are actionable, explainable, and aligned with national health priorities.
5. Data Engineering Support and Pipeline Optimization
The Associate will collaborate with data engineers, integration teams, and AI engineers to:
- Ensure analytical tools and assets are scalable, reproducible, and ready for production.
- Support data pipeline optimization.
- Validate Extract, Transform, and Load (ETL) processes.
- Support readiness for real-time and batch data processing.
6. Mentorship, Capacity Building, and Collaboration
Responsibilities include:
- Mentor junior data scientists and data analysts.
- Lead analytics communities of practice, code reviews, and methodology workshops.
- Review analytical protocols, research designs, and data science deliverables.
- Promote collaboration and high standards across multidisciplinary teams.
7. Innovation and Continuous Improvement
The successful candidate will:
- Keep up to date with developments in machine learning, statistical science, health analytics, artificial intelligence, and causal inference.
- Propose innovative data science applications in public health, health service delivery, health financing, pharmaceutical supply chains, logistics, and disease surveillance.
Qualifications and Experience
Applicants should meet the following requirements:
Educational Qualifications
A Master of Science degree in a relevant discipline, such as:
- Data Science
- Applied Mathematics
- Actuarial Science
- Operations Research
- Statistics
- Epidemiology
- Health Informatics
Professional Experience
- Five to eight years of professional experience in advanced analytics and/or applied statistics, preferably involving data science applications.
- Experience working with large-scale datasets and regulated data environments is required, preferably in the health sector.
Technical Skills
Candidates should demonstrate:
- A strong mathematical foundation.
- Knowledge of statistical methods, including regression, classification, clustering, experimental design, modelling, and advanced forecasting.
- Proficiency in data visualization.
- Practical experience with Python, R, and SQL.
- Experience working with structured, semi-structured, and unstructured datasets.
- The ability to solve loosely defined problems using creative and analytical approaches.
Professional Competencies
Applicants should also demonstrate:
- Strong teamwork and collaboration skills.
- Excellent written and verbal communication.
- The ability to coordinate effectively across multidisciplinary teams.
- Experience mentoring colleagues and leading teams in a fast-paced, changing environment.
Application Deadline
12 October 2026
Regional Human Rights Specialist at WCS – Deadline 30 Oct 2026
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