Senior Data Scientist, Impact Modeling & Analytics

The Bill & Melinda Gates Foundation; Seattle (WA); Presencial; USD 190.000 - 295.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Medical, dental, and vision coverage

Generous paid time off

Paid family leave

Foundation-paid retirement contributed

Regional holidays

Employee communities

Descripción de la vacante

The Bill & Melinda Gates Foundation’s Data & AI Enablement Hub in Seattle, WA seeks a senior data scientist to advance evidence-informed investments through impact accounting, causal modeling, and equity-focused analysis.

You will build reproducible analytical frameworks, translate complex outputs for non-technical audiences, and collaborate with program teams to integrate insights into portfolio planning and grants design, all onsite in Seattle.

Formación

• Advanced degree or equivalent demonstrated experience in a quantitative field.
• Mastery of quantitative modeling methods including causal inference, meta-analysis, effect-size estimation, cost-effectiveness analysis, and predictive modeling.
• Significant experience building analytical models informing investment or strategy decisions in education or social policy.
• Experience serving as a technical resource translating quantitative findings for non-technical audiences.
• Experience creating reproducibility and documentation standards with equity assessment.
• Experience collaborating with program teams and partners to co-develop analytical frameworks.

Responsabilidades

• Build and maintain core impact accounting models, including effect-size extraction frameworks, cost-effectiveness estimates, and scenario analysis tools.
• Lead predictive modeling and forward-looking analyses at strategy, initiative, and work levels.
• Contribute to the Insights Engine for AI Effectiveness by synthesizing research and pilot data.
• Ensure reproducibility, documentation, and equity across modeling approaches.
• Partner with Hub program officers to apply modeling insights in portfolio planning and grant design.
• Translate complex model outputs for non-technical program audiences and leadership.
• Collaborate with measurement and evaluation teams to integrate outputs into governance.

Conocimientos

Causal inference

Meta-analysis

Effect-size estimation

Cost-effectiveness analysis

Predictive modeling

Analytical modeling

Educación

Advanced degree in economics, statistics, public policy, education research, or related quantitative field

Descripción del empleo

The Data & AI Enablement Hub at the Bill & Melinda Gates Foundation works to unlock the full potential of data and artificial intelligence to improve educational and economic outcomes. This role focuses on building impact accounting and analytical modeling capabilities that help teams make evidence-informed investment decisions, with an emphasis on equity-focused, reproducible analysis.

In this Senior Data Scientist position based in Seattle, WA (onsite), you will support strategy and portfolio planning by delivering predictive modeling, effect-size extraction frameworks, cost-effectiveness estimates, and scenario analysis tools. You will also help shape shared modeling standards so colleagues can audit assumptions, interrogate methods, and assess whether models reflect the experiences of historically underserved learner populations.

Responsibilities

• Build and maintain core impact accounting models, including effect-size extraction frameworks, cost-effectiveness estimates, and scenario analysis tools that support investment decisions across the portfolio and track results over time.
• Lead predictive modeling and forward-looking analysis at the strategy, initiative, and body of work levels, enabling program strategy teams and leadership to assess probable impact trajectories and allocate resources with evidence.
• Contribute to the Insights Engine for AI Effectiveness by synthesizing research, market intelligence, and pilot data to surface patterns, risks, and opportunity areas.
• Ensure analytical reproducibility, documentation, and equity across modeling approaches by establishing shared standards for peer review, assumption auditing, and equity assessment of model outputs.
• 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.
• Translate complex model outputs into clear implications for non-technical program audiences and leadership.
• Collaborate with measurement, learning, and evaluation colleagues and division leadership to integrate impact accounting outputs into strategy learning and governance processes, adapting methods as data availability and priorities evolve.
• Identify gaps in analytical infrastructure and initiate development of new modeling capabilities, tools, or data partnerships to strengthen assessment capacity for AI-enabled interventions at scale.
• Support an inclusive culture through modeling behaviors and actions, including timely escalation of issues to the appropriate stakeholders.

Requirements

• Advanced degree or equivalent demonstrated experience, preferably in economics, statistics, public policy, education research, or a related quantitative field.
• Mastery 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 convert research synthesis into decision-ready outputs.
• Significant experience serving as a technical resource to program or leadership teams on impact analysis, cost-effectiveness modeling, and decision analytics, including translating quantitative findings for non-technical audiences.
• Significant experience creating and applying reproducibility and documentation standards, enabling peer review, assumption auditing, and equity assessment.
• 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.
• Unrestricted work authorization in the country where this position is located.
• The Foundation does not provide immigration-related sponsorship for this role, including direct company sponsorship and any work authorization requiring written submission or other immigration support from the company.

Benefits

• Comprehensive medical, dental, and vision coverage with no premiums
• Generous paid time off
• Paid family leave
• Foundation-paid retirement contribution
• Regional holidays
• Opportunities to engage in several employee communities

Salary Range

USD 190,100 - 294,700 per year. The Foundation recognizes wage market differences in Seattle and Washington D.C.; the range for these locations is $209,100 to $324,100 USD. New hires salaries are typically between the range minimum and the midpoint, depending on job-related skills, experience, and expertise as evaluated during the interview process.

Hiring Requirements & Candidate Accommodations

• Employment is contingent upon successful completion of a background check.
• If you have a disability or medical condition and need an accommodation at any stage of the application or interview process, contact [e-mail] with the position number and a brief description of your accommodation needs. Requests are handled confidentially.

Inclusion Statement

The Foundation is dedicated to the belief that all lives have equal value and strives for a global and cultural workplace that supports ever greater diversity, equity, and inclusion. All applicants and employees 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.

The vision 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. The team invests in three catalytic areas: AI solution enablement, trusted evidence for AI in education, and dynamic feedback systems.