Senior Research Economist, Gender, Vulnerability, and Health Equity, Health and Data Systems (11-Month LTE)

Bill & Melinda Gates Foundation•Seattle, WA

2d•$209,100 - $324,100•Onsite

About The Position

The Foundation is 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 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. Your Role We are seeking a full-time Senior Research Economist for a 11-month limited-term position to lead and execute high-impact analytical work focused on cost effectiveness analysis, bundled interventions and health system optimization and prioritization. This role focuses on applying rigorous quantitative and health economic methods to inform decision-making in health systems and service delivery, with an emphasis on women’s health and primary health care including cross-cutting resource allocation and decision modeling. The successful candidate will serve as a core technical lead on specific workstreams, responsible for designing and implementing rigorous health economic and optimization analyses that directly inform policy and investment decisions. They will translate complex research and policy questions into structured analytical strategies that integrate epidemiological dynamics, costs, and health system constraints. This is a hands-on, technically intensive role requiring strong independent execution. The candidate will take ownership of the end-to-end analytical process, from conceptualization through modeling and communication while contributing to the evolution of modeling approaches for optimization and prioritization in constrained health systems. This position is a limited-term position for 11 months. Relocation will not be provided. Application Deadline: June 16, at 11:59pm PDT

Requirements

PhD in a quantitative field such as health economics, economics, statistics, epidemiology, data science, or a related discipline
Minimum of five years of post-PhD experience conducting applied quantitative research in global health economics or related areas
Strong expertise in health economic methods (e.g., cost-effectiveness analysis, resource allocation or optimization), with experience applying these methods to policy-relevant questions
Advanced programming skills in R and/or Python, with demonstrated experience building reproducible, well-structured analytical workflows
Proven ability to independently design and execute complex analyses, from problem formulation through to results interpretation
Experience working with health and data systems, including integrating and analyzing data from sources such as surveys, routine health information systems, facility data, and costing datasets
Experience applying quantitative methods to questions related to health systems strengthening, service delivery, or population health, ideally including women’s, maternal, newborn, or child health
Experience with modeling approaches such as simulation modeling, scenario analysis, or forecasting in applied settings
Demonstrated ability to make sound methodological decisions and adapt approaches based on data availability and real-world constraints
Experience collaborating in interdisciplinary teams and contributing to joint analytical outputs
Strong written communication skills, with the ability to clearly document methods and present findings to technical and non-technical audiences
Strong problem-solving skills and attention to detail
Ability to clearly document and explain analytical approaches and results
Comfortable working in a fast-paced, collaborative research environment
Interest in applying quantitative methods to inform real-world policy and program decisions
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.).

Responsibilities

Lead the design and execution of health economics/resource allocation and optimization analyses to inform prioritization of interventions and health system strategies, particularly in women’s health
Develop and apply cost-effectiveness analyses (CEA) and extended CEA frameworks to inform policy and investment decisions.
Design and conduct modeling approaches such as scenario analysis, forecasting, and simulation to support prioritization across interventions and delivery platforms
Translate high-level research and policy questions into structured analytical approaches and formal decision problems, explicitly incorporating budget, capacity, and delivery constraints
Develop, maintain, and optimize code for data processing, analysis, and modeling (primarily in R and/or Python), ensuring reproducibility and scalability
Independently manage end-to-end analytical workflows, including data cleaning, validation, integration, modeling, and results generation
Work with diverse health and data system inputs (e.g., household surveys, routine health information systems, costing data, facility-level data), addressing challenges such as missingness, bias, and inconsistencies
Conduct sensitivity and uncertainty analyses, and clearly articulate assumptions, limitations, and implications of findings
Collaborate with interdisciplinary teams to refine research questions, align analytical approaches with real-world constraints, and interpret findings in policy-relevant contexts
Produce high-quality analytical outputs, including figures, tables, and technical summaries, and contribute to reports, policy briefs, and other research products
Ensure all analyses are well-documented, transparent, and reproducible, following best practices in code and workflow management