The AI Hub for Maternal, Newborn, and Child Health (MNCH) at LUMS — a multi-institutional initiative supported by the Gates Foundation — is hiring a Research Associate to support data-driven research on maternal and child health outcomes in Pakistan.
Role
The Research Associate will clean, manage, and analyse large health and survey datasets; apply econometric and machine learning techniques; work with multi-source data to map maternal and child health pathways and stakeholder interactions; and support the choice and implementation of estimation approaches through engagement with relevant literature and comparable studies.
- Master's degree in Economics, Public Health, Data Science, or a related field
- Strong quantitative and analytical skills
- Proficiency in Stata (required); familiarity with R or Python is a plus
- Experience with data cleaning, multi-source data integration, and quantitative techniques for understanding pathways, relationships, and outcomes (e.g., descriptive analysis, regression-based approaches, classification and prediction methods)
- Familiarity with machine learning methods
- Ability to work independently, take initiative, and meet deadlines
Send your CV, a brief statement of interest, and a sample of research or analytical work demonstrating your ability to work with quantitative data (e.g., research papers, data analysis projects, or code samples) to warda.riaz@lums.edu.pk by April 16, 2026.