Associate, Data Science

Advanced Data Analytics and Statistical Modelling 

• Lead advanced descriptive, predictive, and inferential analyses across clinical, surveillance, and health systems datasets.
• Develop and validate predictive models, risk stratification algorithms, forecasting models, epidemiological and operational analytics.
• Apply rigorous statistical methods, hypothesis testing, and causal inference techniques to support decision-making.
• Ensure all analytics are clinically interpretable, policy-relevant, and scientifically defensible.

Feature Engineering & Machine Learning Support

• Design robust feature engineering pipelines from EMRs, HMIS, LMIS and surveillance platforms.
• Support AI Engineers with high-quality training datasets, feature selection, bias detection and data representativeness testing.
• Contribute to development of machine learning models, particularly in tabular health data, time-series forecasting and population-level risk prediction.

Data Quality, Governance, and Integrity

• Lead implementation of data quality frameworks, completeness, consistency, accuracy, and timeliness checks.
• Perform data audits, outlier detection, bias and missing data analysis.
• Ensure compliance with national health data governance standards, privacy and ethical data use policies.
• Maintain full data documentation, metadata standards, and lineage tracking.

Health Systems Intelligence & Decision Support

• Develop decision-support analytics and public health dashboards for disease burden tracking, resource allocation and service delivery optimization.
• Translate analytical outputs into policy briefs, executive dashboards, technical report.
• Ensure outputs are actionable, explainable, and aligned with the national health priorities.

Data Engineering Support and Pipeline Optimization

• Work closely with Data engineers, integration teams and AI engineers to ensure analytics assets are scalable, reproducible and production ready.
• Support data pipeline optimization, ETL quality validation and real-time and batch processing readiness.

Mentorship, Capacity Building & Collaboration

• Mentor junior data scientists and analysts.
• Lead internal analytics communities of practice, code reviews and methodology workshops.
• Serve as a technical reviewer for analytics protocols, research designs and data science deliverables.

Innovation and Continuous Improvement

• Stay current with advances in Machine Learning, Statistical Science, Health Analytics, Artificial Intelligence and Causal Inference trends.
• Propose innovative analytics and data science use cases for public health, service delivery, health financing, supply chain and logistics for pharmaceuticals and disease surveillance.

• M.Sc. degree in relevant discipline (Data Science, Applied Mathematics, Actuarial Science, Operations Research, Statistics, Epidemiology, Health Informatics).
• 5–8 years of professional experience in the field of advanced analytics and/or applied statistics preferably with Data Science applications.
• Solid mathematical foundation and knowledge of various statistical methods (e.g. regression, classification, clustering, experimental design, modelling, advanced forecasting).
• Proven experience working with large-scale datasets, regulated data environments, preferably within a health domain.
• Strong proficiency in data visualization, demonstrated experience in Python, R, SQL, and working with structured, semi-structured and unstructured datasets.
• Ability to focus on vaguely defined problems requiring the application of a creative approach.
• Strong teamwork skills.
• Excellent written and verbal communication skills for coordinating across teams.
• Ability to mentor and lead teams in a fast-paced and changing environment.

Application Procedure 

After submitting your CV (maximum 3 pages) through this link, please email a letter of interest (maximum 1 page) outlining how your background meets the requirements outlined above to with " Associate, Data Scientist " in the subject line.

The deadline for applications is October 12, 2026. Only shortlisted candidates will be contacted. 

In compliance with the data protection law of Rwanda and by submitting your application and CV, you explicitly consent to the collection, processing, and storage of your personal data by Clinton Health Access Initiative for the sole purpose of managing and conducting the recruitment process for the position for which you have applied.