Senior Program Officer, AI, Modeling, and Quantitative Methods, Gender Equality

Bill & Melinda Gates Foundation•Seattle, WA

About The Position

The Gender Equality (GE) Division's mission is to ensure women and girls in Africa and South Asia can enjoy good health, make their own choices, earn their own money, and be leaders in their societies. When women and girls have an equal chance to thrive and lead, everyone benefits. Within the GE Division, the Data and Technology Adoption team (DATA) strengthens decision-making to improve the health and well-being of women and girls. Operating as both an investment maker and a functional service provider, the team works across three strategic pillars: providing deep functional expertise to program strategy teams (PSTs) and regional country offices (RCOs) to accelerate impact; developing public goods and platforms with high impact potential and multi-PST relevance; and exploring and incubating new paths to improve women's and girls' health outcomes. This role sits across two of DATA's initiatives: AI Readiness & Innovation, which develops user-experience design intelligence, AI product evaluation frameworks, and frontier innovation; and Modeling & Measurement, which builds locally owned analytics and modeling capacity in low- and middle-income institutions and sustains critical women's health measurement investments. The application deadline for this role is May 13, 2026 at 11:59pm Pacific Time.

Requirements

Ph.D. required in quantitative fields such as Computer Science, Data Science, Engineering, Physics, Public Policy, Biostatistics, Applied Statistics, or related quantitative discipline.
5-10+ years of professional experience in applied AI/ML, digital health product design or evaluation, health measurement, or applied research; ideally, with some experience in LMIC contexts and/or focused on women's and girls' health outcomes.
Strong technical fluency in AI/ML, including familiarity with model architectures, training paradigms, benchmarking approaches, and the current frontier AI landscape, with the ability to move between technical assessment, product design input, and strategic investment decisions about where AI can deliver impact for women and girls.
Hands-on experience helping shape, develop, or deploy AI-enabled tools or products, ideally in LMIC settings. This includes influencing what gets built, how it is designed, what data and infrastructure are needed, and how it fits into end-user contexts, with enough technical depth to assess feasibility, cost tradeoffs, and provider selection for technically complex proposals.
Demonstrated expertise in one or more of the following: AI product design or evaluation, AI safety and equity assessment, applied modeling and forecasting, mixed-methods research, or gender-disaggregated health measurement.
Demonstrated ability to engage with frontier AI labs, major technology companies, or technical standards bodies, translating between cutting-edge AI capabilities and the equity, safety, and relevance concerns of LMIC populations and gender equality goals.
Ability to critically evaluate how AI systems and tools are being assessed, including benchmarks, red-teaming, bias audits, and safety evaluations, and to develop an independent point of view on what constitutes credible, equity-centered evidence of AI impact, distinct from traditional evaluation approaches.
Experience identifying, scoping, and originating philanthropic or research investments, including sourcing partners, conducting due diligence, negotiating agreements, and managing investment budgets in LMICs.
Comfort operating at pace across multiple workstreams, geographies, and technical domains simultaneously, with the judgment to prioritize and the discipline to follow through.
Track record of working with country-level partners, including government agencies, academic institutions, and regional offices, to co-design and implement research or data initiatives grounded in local priorities.
Familiarity with maternal and child health and/or infectious disease evidence landscapes, and with key datasets and research institutions relevant to women and girls in Sub-Saharan Africa and South Asia.
Demonstrated ability to navigate ambiguity, incubate new areas of inquiry, and move from identifying evidence gaps to building funded research agendas.
Demonstrated ability to work across topics, sectors, or fields, such as health, technology, economics, and gender, synthesizing diverse evidence streams into coherent investment strategies.
Proven relationship builder with experience cultivating and managing partnerships across government agencies, academic institutions, multilateral organizations, and regional or country offices in LMICs.
Comfort operating as a trusted partner to country-level stakeholders, not just a funder.
Strong communication skills, including the ability to translate complex technical findings for diverse audiences including senior leadership, and a track record of contributing to field-level discourse through convenings, publications, or strategic partnerships.
Ability to travel up to 30% domestically and internationally.

Responsibilities

Serve as the DATA team's primary AI technical voice: tracking frontier AI developments, translating their implications for gender equality and women's health, and advising GE leadership on where the field is headed, what matters, and where GE can lead.
Engage credibly with frontier AI labs and major technology companies on behalf of the foundation: assessing partnership opportunities, informing advocacy positions on equity and safety, and identifying where GE engagement can shape how AI systems are built and evaluated for LMIC populations.
Provide investment-grade technical diligence on AI proposals, evaluating feasibility, cost, provider selection, and build-vs-buy tradeoffs; advise on where foundation investment is needed versus where the field is likely to advance on its own.
Incubate research in understudied areas that affect women's maternal and child health outcomes, and the use of large language models to improve health information delivery in low-literacy settings.
Shape the design, testing, and evaluation of AI-powered products for vulnerable populations with emphasis on influencing what gets built and how (not only measuring what exists) including advising on data requirements, model architecture choices, and end-user fit.
Critically assess how AI systems are being measured and benchmarked for equity, safety, and real-world impact, and develop GE's own approach to evaluating AI products across the portfolio, one that builds cumulative learning, validates for accuracy and fairness in LMIC contexts, and is distinct from conventional evaluation paradigms.
Manage and oversee a portfolio of investments — grants, contracts, and partnerships — across both initiatives, including budget oversight and financial tracking, monitor progress and report to leadership on results and emerging risks.
Partner with regional and country offices and other program teams to co-develop modeling and AI investments aligned to local priorities and programmatic strategies, translating country-level evidence gaps into funded initiatives (e.g., data generation, model validation, in-country benchmarking) and bridging technical capabilities with programmatic goals across DATA, MNCNH, and country offices.
Oversee applied analytics, forecasting, and mathematical modeling investments, including support for country-led consortia and the integration of AI capabilities into country health information systems while maintaining a portfolio-level view on which modeling and AI investments merit continued funding.
Interpret and present data and research results to audiences with varying technical expertise, including senior leadership, to support data-driven decision-making.
Represent and raise the profile of the DATA team in external convenings and actively shape discourse in the AI-for-development, responsible AI, and women's health measurement fields through partnerships, publications, and strategic engagement.
Other duties as assigned.