Senior Research Scientist (Global Health Modeling)

TL;DR

Senior Research Scientist (Global Health Modeling): Design and implement applied statistical analyses to address population-level questions in demography, socioeconomic dynamics, and public health outcomes with an accent on forecasting and time-series models. Focus on analyzing complex real-world datasets, extrapolating intervention effectiveness across contexts, and quantifying uncertainty for strategic decision-making.

Seattle, WA (full-time onsite). Must have unrestricted work authorization in the US. The Foundation does not provide immigration-related sponsorship. Relocation will be provided. Some international travel may be required.

$209,100 to $324,100 USD (Seattle)

Company

Largest nonprofit fighting poverty, disease, and inequity worldwide via computational modeling tools for global disease eradication.

What you will do

• Design and implement applied statistical analyses for demography, socioeconomic dynamics, and public health outcomes
• Develop forecasting and time-series models for planning, scenario analysis, and decision-making
• Analyze complex datasets from surveys, surveillance, and programmatic sources with missingness or bias
• Extrapolate evidence on intervention effectiveness to new contexts for program scale-up projections
• Quantify and communicate assumptions, uncertainty, and limitations to technical and non-technical audiences
• Collaborate with interdisciplinary teams to co-develop research and translate results into actionable insights
• Contribute to research outputs like reports, policy briefs, and publications with reproducible code

Requirements

• PhD in statistics, biostatistics, or related quantitative discipline (e.g., mathematical demography, economics, data science)
• Minimum 5 years post-PhD experience in applied statistical research for public health or population-level settings
• Experience applying stats to demographic, socioeconomic, and health research questions
• Strong expertise in forecasting, time-series analysis, model validation, and uncertainty quantification
• Advanced Python and R skills for reproducible, scalable analytical workflows
• Ability to work with messy, incomplete real-world data in interdisciplinary environments
• Unrestricted US work authorization required; no sponsorship

Nice to have

• Experience in global health and low- and middle-income countries
• Strong communication skills for diverse audiences

Culture & Benefits

• Comprehensive medical, dental, vision coverage with no premiums
• Generous paid time off, paid family leave, foundation-paid retirement contributions
• Regional holidays and employee communities
• Dynamic, innovative, collaborative environment with global partnerships
• 2-year limited-term position