Data Scientist

AIR is seeking a Data Scientist to join the Project Success and Innovation (PSI) team and the Employment and Economic Opportunity Program (EEOP), providing advanced technical expertise to support innovation development, scaling efforts, and applied research and analytics across project teams. Within PSI, the Data Scientist will contribute to AIR’s Innovation Lab by co-designing, developing, and scaling solutions that strengthen and amplify effective practices across diverse technical and operational workflows.

Within EEOP, the Data Scientist will lead end-to-end quantitative workflows, including establishing and maintaining reproducible analytic environments, managing and quality assuring complex datasets, reviewing and strengthening junior staff members’ code, and conducting advanced statistical analyses. These analyses may include causal approaches, such as experimental and quasi-experimental designs, as well as non-causal approaches, including descriptive, predictive, and explanatory modeling. The Data Scientist will also help expand AIR’s capacity to responsibly apply machine learning methods in support of both research and operational objectives, while translating technical findings into clear, actionable products for clients, partners, and other stakeholders.

Candidates hired for the position may work remotely within the United States (U.S.) or from one of our U.S. office locations. This does not include U.S. territories.

About AIR:

Founded in 1946 and headquartered in Arlington, Virginia, the American Institutes for Research (AIR) is a nonpartisan, not-for-profit organization that conducts behavioral and social science research and delivers technical assistance to address some of the most pressing challenges in the United States and globally. We generate evidence and apply data-driven solutions that expand opportunities and improve lives for all.

Responsibilities

The responsibilities for the position include:

PSI (approximately 50_%)_

• Build and maintain shared analytic tools, including code libraries, project templates, and pipelines, that research teams across AIR can adopt and reuse.
• Write documentation, training materials, and onboarding guides that make modern tooling accessible to staff with varying levels of technical experience.
• Support project teams adopting new tools and workflows by answering questions, troubleshooting, and relaying recurring problems back to the team.
• Prototype and test new tools and platforms, including machine learning and AI applications such as large language models, and help assess their fit and responsible use at AIR.
• Help maintain deployed tools by triaging issues, fixing bugs, and tracking user feedback.