Senior Research Scientist, Global Health Modeling (2-year LTE)

Bill & Melinda Gates Foundation•Seattle, WA

About The Position

We are the largest nonprofit fighting poverty, disease, and inequity around the world. Founded on a simple premise: people everywhere, regardless of identity or circumstances, should have the chance to live healthy, productive lives. We believe our employees should reflect the rich diversity of the global populations we aim to serve. We provide an exceptional benefits package to employees and their families which include comprehensive medical, dental, and vision coverage with no premiums, generous paid time off, paid family leave, foundation-paid retirement contribution, regional holidays, and opportunities to engage in several employee communities. As a workplace, we’re committed to creating an environment for you to thrive both personally and professionally. As part of the Gates Foundation (GF), the Institute for Disease Modeling (IDM) mission is to support global efforts to eradicate infectious diseases and achieve permanent improvements in health by developing, using, and sharing computational modeling tools and promoting quantitative decision-making. The IDM team is composed of research scientists and software developers who create advanced models of disease transmission, develop computational tools to inform global disease eradication policy, conduct analysis of epidemiologically- and policy-relevant data, and identify and address critical knowledge gaps. IDM is a highly dynamic organization with a work environment that is defined by innovation and collaboration. As part of our work, we routinely collaborate with international health agencies, ministries of health in the developing world, as well as universities and research institutes across the globe. This position is a limited-term position for 2 years. Relocation will be provided. In this role, we seek a full-time Senior Research Scientist to join IDM’s Gender, Vulnerability and Health Equity (GVHE) research team with deep expertise in applied statistics for population health research. This role is ideal for a statistician who excels at applying advanced statistical methods to demographic, socioeconomic, and health-related questions, with a strong emphasis on forecasting and time-series analysis. The successful candidate will focus on generating practical, interpretable insights from complex data to inform public health strategy and policy. Candidates whose primary background is in theoretical statistics, biological systems modeling, or clinical trials–focused biostatistics are unlikely to be a good fit.

Requirements

PhD in statistics, biostatistics or related quantitative discipline (e.g., mathematical demography, economics, data science, etc.)
Minimum of five (5) years of post-PhD experience conducting applied statistical research in public health or population-level research settings
Demonstrated experience applying statistical methods to demographic, socioeconomic, and health-related research questions
Strong expertise in forecasting and time-series analysis, including model validation, uncertainty quantification and scenario-based analysis
Advanced skills in Python and R, with experience developing reproducible and scalable analytical workflows
Proven ability to work with messy, incomplete, and imperfect real-world data
Experience collaborating in interdisciplinary and cross-sector research environments
Strong written and verbal communication skills, with the ability to explain statistical findings clearly to diverse audiences
Must have unrestricted work authorization in the country where this position is located. The Foundation does not provide immigration-related sponsorship for this role. This includes direct company sponsorship and any work authorization requiring a written submission or other immigration support from the company (eg: H-1B, O-1, L-1, E, OPT, STEM-OPT, CPT, TN, J-1, etc.).

Nice To Haves

Experience working in global health and low- and middle-income countries is a plus

Responsibilities

Design and implement applied statistical analyses to address population-level questions related to demography, socioeconomic dynamics, and public health outcomes
Develop and apply forecasting and time-series models to inform planning, scenario analysis, and strategic decision-making
Analyze complex, real-world datasets (e.g., surveys, surveillance systems, administrative and programmatic data), often characterized by missingness, bias, or measurement limitations
Apply advanced modeling methods to extrapolate evidence on program/ intervention effectiveness to different contexts and populations, generating rigorous projections to inform program scale-up and future investment planning
Quantify and communicate assumptions, uncertainty, and limitations of analyses to both technical and non-technical audiences
Collaborate closely with interdisciplinary teams to co-develop research questions and analytical approaches
Translate statistical results into clear, actionable insights for internal stakeholders and external partners
Contribute to high-quality applied research outputs, including internal reports, policy briefs, and peer-reviewed publications
Support reproducible research practices through well-documented, maintainable code and analytical workflows
Some international travel may be required