Senior Research Scientist, Population Health Modeling, Nutrition and Disease

Job Posting Organization:
The Gates Foundation is the largest nonprofit organization dedicated to fighting poverty, disease, and inequity globally. Founded on the principle that all individuals, regardless of their identity or circumstances, deserve the opportunity to lead healthy and productive lives, the Foundation emphasizes diversity among its employees to reflect the global populations it serves. The organization offers an exceptional benefits package that includes comprehensive medical, dental, and vision coverage with no premiums, generous paid time off, paid family leave, retirement contributions, regional holidays, and opportunities for employees to engage in various community initiatives. The Foundation is committed to fostering an environment that supports both personal and professional growth for its employees.

Job Overview:
The Senior Research Scientist position is a full-time role within the Institute for Disease Modeling (IDM) at the Gates Foundation, specifically within the Gender, Vulnerability and Health Equity (GVHE) research team. The ideal candidate will possess deep expertise in applied statistics, particularly in the context of population health research. This role is designed for a statistician who is adept at utilizing advanced statistical methods to address demographic, socioeconomic, and health-related questions, with a strong focus on forecasting and time-series analysis. The successful candidate will be responsible for generating practical insights from complex datasets to inform public health strategies and policies. Candidates with a background primarily in theoretical statistics, biological systems modeling, or clinical trials-focused biostatistics may not be suitable for this position. This is a limited-term position for two years, and relocation assistance will be provided.

Duties and Responsibilities:
The Senior Research Scientist will be tasked with designing and implementing applied statistical analyses to tackle population-level questions related to demography, socioeconomic dynamics, and public health outcomes. Responsibilities include developing and applying forecasting and time-series models to support planning and strategic decision-making, analyzing complex datasets that may have issues such as missing data or measurement limitations, and applying advanced modeling techniques to extrapolate evidence on program effectiveness across different contexts. The role also involves quantifying and communicating assumptions, uncertainties, and limitations of analyses to both technical and non-technical audiences, collaborating with interdisciplinary teams to co-develop research questions, and translating statistical results into actionable insights for stakeholders. Additionally, the scientist will contribute to high-quality research outputs, including internal reports, policy briefs, and peer-reviewed publications, while supporting reproducible research practices through well-documented code and analytical workflows. Some international travel may be required as part of the role.

Required Qualifications:
Candidates must hold a PhD in statistics, biostatistics, or a related quantitative discipline such as mathematical demography, economics, or data science. A minimum of five years of post-PhD experience in conducting applied statistical research in public health or population-level research settings is required. Demonstrated experience in applying statistical methods to demographic, socioeconomic, and health-related research questions is essential, along with strong expertise in forecasting and time-series analysis, including model validation and uncertainty quantification. Advanced skills in programming languages such as Python and R are necessary, as well as experience in developing reproducible and scalable analytical workflows. The ability to work with messy, incomplete, and imperfect real-world data is crucial, and experience in interdisciplinary and cross-sector research environments is highly valued.

Educational Background:
The educational requirement for this position is a PhD in statistics, biostatistics, or a closely related quantitative field. This advanced degree is essential for the candidate to possess the necessary theoretical knowledge and practical skills to perform the complex statistical analyses required for the role.

Experience:
The position requires a minimum of five years of post-PhD experience in applied statistical research, specifically within public health or population-level research contexts. This experience should demonstrate the candidate's ability to apply statistical methods effectively to real-world health-related questions and datasets.

Languages:
While the job description does not specify mandatory languages, strong written and verbal communication skills in English are essential for explaining statistical findings to diverse audiences. Proficiency in additional languages may be beneficial, particularly in the context of global health and collaboration with international partners.

Additional Notes:
This is a limited-term position for two years, and relocation assistance will be provided. The salary range for this role is between $190,100 to $294,700 USD, with higher ranges for positions based in Seattle and Washington D.C. The Foundation emphasizes a balance between competitive pay and its mission-driven objectives. New hire salaries typically fall between the minimum and midpoint of the salary range, depending on the candidate's skills, experience, and expertise as assessed during the interview process. Employment is contingent upon successful completion of a background check, and the Foundation is committed to providing an inclusive and accessible hiring experience for all candidates.