Senior Data Scientist, Impact Modeling & Analytics - US Program

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 Data & AI Enablement Hub works to unlock the full potential of data and artificial intelligence to improve educational and economic outcomes. Our vision is that by 2045, all learners and the people who support them will be empowered by safe, evidence-based, AI-enabled solutions that deliver personalized experiences and universally recognized skills, so they can navigate pathways, move across institutions, and thrive in meaningful work. To achieve this, we invest in three catalytic areas: AI solution enablement, trusted evidence for AI in education, and dynamic feedback systems. We amplify this work through investing in focus geographies, driving strategic partnerships with frontier AI labs and co-funders, and partnering with other teams within U.S. Program in using data and AI to drive equitable impact.

Your Role 

You are responsible for building and maintaining the impact accounting and analytical modeling capabilities that underpin data-driven investment decisions across the strategy. You develop predictive models, effect-size extraction frameworks, and cost-effectiveness estimates that support measurement, learning, and evaluation functions and scenario analysis at the strategy, initiative, and body of work levels. You have mastery-level knowledge of quantitative modeling methods, causal inference, and applied research synthesis, and you ensure that all analytical approaches are reproducible, well-documented, and designed to surface equitable outcomes for the learners the foundation serves. 

What You’ll Do 

• Build and maintain core impact accounting models—including effect-size extraction frameworks, cost-effectiveness estimates, and scenario analysis tools—that support investment decision-making across the portfolio, applying rigorous standards to identify specific measurable outcomes and track results over time. 

• Lead predictive modeling and forward-looking analysis at the strategy, initiative, and body of work levels, producing outputs that enable program strategy teams and leadership to assess probable impact trajectories and make evidence-informed resource allocation decisions. 

• Contribute to the Insights Engine for AI Effectiveness by synthesizing research, market intelligence, and pilot data to surface patterns, risks, and opportunity areas—drawing on innovative thinking to identify signals that inform both near-term portfolio adjustments and longer-term strategic direction. 

• Ensure analytical reproducibility, documentation, and equity across all modeling approaches, building shared standards that allow colleagues to interrogate assumptions, audit methods, and assess whether models adequately account for the experiences of historically underserved learner populations. 

• Partner with Hub program officers and program strategy teams to apply modeling insights in portfolio planning and grant design, translating quantitative findings into actionable guidance through a collaborative and stakeholder-centered approach. 

• Translate complex model outputs into accessible implications for non-technical program audiences and leadership, communicating openly and clearly so that analytical insights reach the people best positioned to act on them. 

• Collaborate with measurement, learning, and evaluation colleagues and division leadership on integrating impact accounting outputs into strategy learning and governance processes, adapting methods with resilience as data availability, strategic priorities, and field evidence evolve. 

• Identify gaps in current analytical infrastructure and initiate action to develop new modeling capabilities, tools, or data partnerships that strengthen the foundation’s capacity to assess AI-enabled interventions at scale. 

• Support inclusive culture through modeling behaviors and actions; escalate issues in a timely fashion to appropriate stakeholders. 

 

Your Experience 

• An Advanced degree or equivalent demonstrated experience, preferably in economics, statistics, public policy, education research, or a related quantitative field. 

• Mastery level knowledge of quantitative modeling methods relevant to education and social impact contexts, including causal inference, meta-analysis, effect-size estimation, cost-effectiveness analysis, and predictive modeling. 

• Significant experience building and maintaining analytical models that inform investment or program strategy decisions in education, social policy, or adjacent fields, with demonstrated ability to move from research synthesis to decision-relevant outputs. 

• Significant experience as a technical resource to program or leadership teams on impact analysis, cost-effectiveness modeling, and decision analytics, including translating complex quantitative findings for non-technical audiences. 

• Experience developing and applying reproducibility and documentation standards for analytical work, including practices that enable peer review, assumption auditing, and equity assessment of model outputs. 

• Significant experience building collaborative partnerships with program teams, researchers, or institutional partners to co-develop analytical frameworks and integrate modeling insights into planning and governance processes. 

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 (e.g. H-1B, O-1, L-1, E, OPT, STEM-OPT, CPT, TN, J-1, etc.).

The salary range for this role is $190,100 to $294,700 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 $209,100 to $324,100 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.

#LI-AD1

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

We’re committed to providing an inclusive and accessible hiring experience for all candidates. If you have a disability or medical condition and need an accommodation at any stage of the application or interview process—such as an ASL interpreter, alternative interview format, or physical accessibility support—we’re happy to help. Please contact HR@gatesfoundation.org with the position number and a brief description of your accommodation needs. Requests will be handled confidentially.

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.