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. We aim to develop reusable resources and support capacity strengthening to maximize our impact at the foundation and larger global health community.

Your Role

The Research Scientist will apply modeling approaches to maximize the value of surveillance and diagnostics data for decision-making across local and regional scales. The inherent complexity of these data requires the ability to integrate multiple factors - including policymaker priorities, local resources, data biases, diagnostic sensitivity, and epidemiological dynamics - into models that generate useful insights. This position calls for a ‘wide lens’ perspective, balancing site-specific realities with broader methodological approaches to strengthen surveillance from the ground-up. The successful candidate will also contribute to the development of tools and methods that support and expand the use of surveillance and diagnostic data in policy feedback loops. As a cross-cutting role, the position will engage with disease-specific program and IDM teams, as well as surveillance partners on the ground. Ultimately, this work will support and advance IDM’s long-term surveillance initiative, with a focus on innovation, generalizability, and resourcefulness.

What You’ll Do

• Execute on key surveillance pilot projects spanning TB, nutrition, and enteric/diarrheal diseases
• Align key public health questions with appropriate modeling solutions
• Identify and apply effective and rigorous statistical techniques to address key questions, including custom analytical approaches and existing IDM tools
• Contribute to site selection by assessing strategic focal areas, data availability and quality, partner engagement, and program team support
• Collaborate with team members to accelerate existing workstreams
• Keep a ‘birds-eye’ view across disparate projects to help drive long-term surveillance strategy and inform technical gaps
• Implement best practices for LMIC surveillance collaborations, ensuring effective communication of results, and supporting translation of work into impact and policy
• Build and sustain relationships with key collaborators in surveillance and diagnostics, including travel as needed
• Maintain knowledge of emerging scientific literature and awareness of cross-IDM and program team surveillance efforts

Your Experience

• PhD or equivalent experience required in quantitative epidemiology, statistics or a related field
• Demonstrated experience in statistical methods: exploratory data analysis, geostatistical modeling, time series analysis, and multivariate analyses, with proven ability to interpret and communicate model uncertainty
• Extensive experience working in LMIC settings, including health systems at local or regional scale. Experience identifying innovative approaches for complex challenges, translating modeling results to on-the-ground solutions, implementing changes to maximize impact
• Demonstrated ability to design and apply modeling approaches to address diverse and complex challenges
• Strong programming skills in R; proficiency in Python, MATLAB, or C++ is an asset

Other Attributes

• Ability to identify common themes and opportunities across complex and diverse topics
• Strong skills in scientific communication through presentations and peer-reviewed publications
• Curiosity and comfort working in ambiguous or evolving contexts
• Demonstrated ability to translate complex analyses into clear, concise policy recommendations, and to engage effectively with diverse stakeholders

Please apply with CV and cover letter.

The salary range for this role is $169,700 to $254,500 USD. We recognize high-wage market differences in Seattle and Washington D.C., where our offices are located. The range for this role in these locations is $185,000 to $277,400 USD. As a mission-driven organization, we strive to balance competitive pay with our mission. New hires salaries are typically between the range minimum and the salary range midpoint. Actual placement in the range will depend on a candidate’s job-related skills, experience, and expertise, as evaluated during the interview process.

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Hiring Requirements

As part of our standard hiring process for new employees, employment will be contingent upon successful completion of a background check.

Candidate Accommodations

If you require assistance due to a disability in the application or recruitment process, please submit a request here.

Inclusion Statement

We are dedicated to the belief that all lives have equal value. We strive for a global and cultural workplace that supports ever greater diversity, equity, and inclusion — of voices, ideas, and approaches — and we support this diversity through all our employment practices.

All applicants and employees who are drawn to serve our mission will enjoy equality of opportunity and fair treatment without regard to race, color, age, religion, pregnancy, sex, sexual orientation, disability, gender identity, gender expression, national origin, genetic information, veteran status, marital status, and prior protected activity.