Postdoctoral Associate - Clinical Epidemiology

Job Duties

• Supports the construction and maintenance of data pipelines. Maintains and further develops the existing data pipeline used for Monitoring & Evaluation (M&E) of the Global HOPE initiative, ensuring data integrity across partner sites in Sub-Saharan Africa.
• Designs and builds interactive data dashboards to visualize key performance indicators, patient volumes, and program outcomes for stakeholders. Develops dashboards for program operations and research.
• Designs and develops statistical analysis for research. Analyzes programmatic data to support the Global HOPE mission of training pediatric hematologist-oncologists and building treatment capacity in partner countries.
• Assists in interpretation of data.
• Investigates treatment-associated toxicities using clinical data to develop predictive risk models.
• Applies survival analysis techniques to evaluate long-term outcomes in diverse pediatric patient populations.
• Leads production of scientific abstracts and manuscripts for scientific community.
• Contributes to grant writing and study development.
• Leads the writing and prepares manuscripts for peer-reviewed journals and present findings at national and international conferences.
• Provides technical guidance to junior data analysts or research coordinators, but primarily an individual contributor role.
• Performs other job-duties as assigned.

Minimum Qualifications

• MD or Ph.D. in Basic Science, Health Science, or a related field.
• No experience required.

Preferred Qualifications

• PhD in Epidemiology, Biostatistics, Data Science, Bioinformatics, or a related field; OR an MD with a strong quantitative background/Master’s degree in a quantitative field.
• Experience developing data dashboards (e.g., Shiny, Dash, Tableau, or PowerBI).
• Strong background in survival analysis and regression modeling.
• Experience with data engineering or maintaining data pipelines (ETL processes).
• Experience in Global Health or working with international datasets (specifically Sub-Saharan Africa).
• Prior experience with clinical or healthcare data (EHR, registries).
• High proficiency in coding with R or Python for data cleaning, analysis, and visualization.