Senior Research Scientist, Disease Modeling

The Foundation

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.

The Team
The goals of IDM's Modeling, Integrated Surveillance, and Translational science (MIST) team are to utilize mechanistic modeling, statistical analyses, and tailored approaches to accelerate impact and optimize systems. We utilize a cross-cutting lens for surveillance and diagnostics to inform disease verticals such as enteric and diarrheal diseases and TB, as well as engagements across AMR, nutrition, and gut microbiome. Our work informs strategic investments within the foundation, and we often partner with the broader global health community to maximize our impact.

Your Role

The Senior Research Scientist will work to maximize the value of surveillance and diagnostic data for decision-making at local and regional levels. This includes quantitatively assessing the robustness of existing systems and contributing to the design of sustainable surveillance systems for the future. Because surveillance data systems are inherently complex, this role requires the ability to integrate multiple factors-such as policymaker priorities, local resources, bias, diagnostic sensitivity, and epidemiological dynamics-and identify the key drivers of system performance and success.

The position requires a broad, systems-level perspective to navigate across site-specific challenges and pathogen-specific differences, with an ability to dive deep into analytical solutions where needed. The role will also focus on advancing tools and methods that better integrate surveillance data across systems and into policy feedback loops. Success requires methodological flexibility, creativity, and adaptability to new questions and concepts. As a cross-cutting position, the Senior Research Scientist will collaborate closely with disease-specific program teams and IDM colleagues, while partnering deeply with on-the-ground surveillance systems.

This work will contribute to the development of a long-term surveillance initiative at IDM centered on innovation, generalizability, and resourcefulness.

What You'll Do

• Execute on key surveillance pilot projects spanning TB, nutrition, and cross-pathogen systems
• Rapidly identify key gaps and questions in surveillance systems, and align appropriate modeling solutions
• Engage on cross-foundation initiatives to advise on statistical power, dynamic systems, and data integration
• Identify and apply effective and rigorous statistical techniques, including customized approaches and existing IDM tools
• Collaborate with team members to accelerate existing work streams in surveillance
• Keep a 'birds-eye' view across disparate projects to help drive long-term surveillance strategy and inform technical gaps
• Advocate for best practices for LMIC surveillance collaborations, ensuring effective communication of results, and uptake/ acceptance of work to translate to impact or policy
• Grow and maintain collaborator relationships for key initiatives in surveillance and diagnostics, including travel as required
• Maintain knowledge of ongoing literature in the field and awareness of cross-IDM and program team surveillance efforts

Your Experience

• PhD or equivalent experience required in subjects relevant to quantitative epidemiology and statistics
• 5+ years professional experience in statistical methods or dynamic modeling, including mixed-effects, geostatistical, time series modeling, and mechanistic models
• Experience with using AI for modeling or surveillance systems an asset
• Demonstrated success in scientific communication through peer reviewed publication, including effective interpretation and communication of model uncertainty
• Strong programming skills in R. Additional skills using Stan or Python an asset
• Demonstrated experience and enthusiasm linking complex modeling approaches to real-world impact, ability to translate complex work and outcomes to concise policy recommendations
• Experience with quantitative engagements in LMIC contexts for public health, with a focus on health systems at local or regional scale

Other Attributes

• Curiosity and tolerance for ambiguity
• Strong preference given to those willing to relocate to Seattle.

Please apply with CV and cover letter for consideration.

The salary range for this role is $190,100 to $294,700 USD. We recognize high-wage market…