Senior Global Health Development Economist

This is a fully remote position, open to applicants in California, +4 more states.

📋 Description

• Act as a liaison among data scientists, economists, and domain experts, facilitating communication across disciplines to ensure that analytical methodologies are both methodologically sound and relevant to real-world development and global health issues.

• Create and execute quantitative analyses to tackle global health challenges in low- and middle-income countries, emphasizing predictive analytics, geospatial analyses, and causal design.

• Utilize machine learning and AI methodologies, including predictive analytics, on real-world datasets (e.g., AIR’s malaria early warning system and other geospatial or satellite data) to produce forward-looking insights and foster innovative, data-driven solutions in global health and development settings.

• Design and implement machine learning and predictive analytics workflows using Python (and, when suitable, R) to analyze intricate development and global health data.

• Integrate and scrutinize survey, administrative, and remotely sensed data (e.g., satellite or geospatial) to yield novel insights into development and global health issues.

• Contribute to the planning and execution of applied research studies, incorporating experimental and quasi-experimental methodologies where applicable.

• Translate complex analytical findings into clear, actionable recommendations for policymakers, program implementers, and funders.

• Collaborate with interdisciplinary teams, including economists, data scientists, and sector specialists, to embed data-driven methodologies into projects.

• Assist in business development initiatives, including drafting technical approaches, shaping analytical strategies for proposals, and engaging with donors such as the Gates Foundation, World Bank, U.S. Department of State, UNICEF, and other collaborators.

• Interact with partners and stakeholders in Low- and Middle-Income Countries (LMICs) to ensure analyses are rooted in contextual realities and implementation challenges.

• Mentor and guide junior researchers and data scientists, promoting professional development and technical proficiency.

• Oversee multidisciplinary project teams and guarantee high-quality deliverables that meet client expectations.

⛳️ Requirements

• Ph.D. in Economics, Computer Science, Data Science, Public Policy, Global Health, or a related quantitative or social science discipline, with proven expertise in econometrics, machine learning, computer science, applied statistics, or quantitative data science. A Master's degree in one of these fields, along with at least five years of relevant experience, may be accepted as an alternative to a Ph.D.

• At least 3 years of experience in conducting quantitative research in policy-relevant fields.

• Extensive proficiency in Python and R; familiarity with Stata is also required.

• Documented success in designing and implementing data analytics tools, such as forecasting models, geospatial analyses, or Large Language Model (LLM) frameworks.

• Previous research experience in areas such as development economics, health economics, global health, or broader international development.

• Experience managing complex projects and collaborating with government, nonprofit, or philanthropic clients.

• Background in business development and fundraising with nonprofit organizations, government entities, or multilateral agencies within the global health sector.

🏝️ Benefits

• Health insurance

• 401(k) matching

• Flexible work hours

• Paid time off

• Remote work options