BESAFE Data Analyst and Modeler

We are seeking a BESAFE Data Analyst and Modeler to support the Burden and Effects of Substandard and Falsified Medicines Exposures (BE SAFE) study which seeks to fill this critical evidence gap by quantifying the impact of SF medicines on maternal and child mortality and estimating quality-adjusted life years (QALYs) lost and potentially gained from eliminating this burden. Generating such evidence is essential for informing national and global policy responses, guiding resource allocation, and strengthening pharmaceutical regulatory systems to protect the most vulnerable populations. Working in close collaboration with the Principal Investigator and co-Investigators, the analyst will lead the development and implementation of modeling frameworks, conduct advanced data analysis, and contribute to the production of high-impact research outputs. The role requires a strong foundation in epidemiological modeling, economic analysis, analytical interpretation and data translation.

Specific Duties & Responsibilities

• Collaborate with the PI and research team to design and implement modeling strategies to estimate morbidity, mortality, and economic burden attributable to SF medicines.
• Clean, manage, and analyze large datasets from sources such as Demographic and Health Surveys (DHS), national surveillance systems, WHO databases, and peer-reviewed literature.
• Apply counterfactual modeling techniques, decision-tree analysis, and cost-effectiveness frameworks to estimate the impact of improved medicine quality.
• Build and validate models simulating outcomes under various regulatory scenarios and intervention strategies, including improvements in post-marketing surveillance and risk-based inspection.
• Conduct sub-analyses by country, therapeutic area, and medicine type, including sensitivity and uncertainty analyses.
• Generate data visualizations, figures, and dashboards to communicate key findings to technical and non-technical audiences.
• Support manuscript development, technical reports, donor updates, and policy briefs.
• Document and maintain reproducible workflows and code using version control systems.
• Contribute to the development of methods for machine learning-based classification of risk factors for SF medicine prevalence (optional based on skill set).
• Engage with national and international partners to ensure alignment of model assumptions with field realities and regulatory priorities.

• Master's Degree in related discipline. Typically require PhD.
• One-year related experience. Require highly specialized advanced knowledge, education and/or training in a specialized field of study to conduct research.

• Master’s Degree or PhD in Public Health.
• Relevant training in Health Economics or related field.
• Demonstrated experience in quantitative data analysis, epidemiological or economic modeling, and health systems research.
• Proficiency with statistical software (e.g., Stata, R, or Python) and data visualization tools.
• Familiarity with global health datasets such as DHS, IHME, WHO GHO, and regulatory surveillance data.
• Experience working with counterfactual analysis, burden of disease modeling, or cost-effectiveness studies.
• Knowledge of medicine quality issues and regulatory systems in low- and middle-income countries is a plus.

Classified Title: Sr. Research Data Analyst 
Job Posting Title (Working Title): BESAFE Data Analyst and Modeler   
Role/Level/Range: ACRP/04/MD  
Starting Salary Range: $26.82 - $46.92 HRLY (Commensurate w/exp.) 
Employee group: Casual / On Call 
Schedule: Hours Vary; Approximately 20 hours/week 
FLSA Status: Exempt 
Location: Hybrid: On-site 1-2 days a week 
Department name: 10001156-Popltn Fmly and Reproductive Hlth Srvs 
Personnel area: School of Public Health