Data Scientist, Learning Supports

AIR is seeking a Data Scientist to join the Learning Supports program and provide foundational and advanced analytic support across multiple project teams. The Data Scientist will take ownership of end-to-end quantitative workflows—setting up and maintaining reproducible analytic environments, managing and quality-checking complex datasets, reviewing and strengthening junior analysts’ code, and leading inferential modeling tasks spanning both causal (e.g., experimental and quasi-experimental designs) and non-causal (e.g., descriptive, predictive, and explanatory) analyses. The role will also help expand AIR’s capacity to responsibly apply machine learning methods in support of causal and non-causal work, while translating technical results into clear, decision-relevant products for clients and stakeholders. The Data Scientist will join AIR’s Learning Supports program, which conducts research, evaluation, and implementation support for federal and state agencies, school districts, and foundations. The program produces rigorous evidence and practical tools to inform policy and practice, helping ensure early and equitable access to learning and the supports children and families need to succeed. This position has the flexibility to work remotely within the United States (U.S.) or from one of AIR’s 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

• Lead or contribute to the design and execution of rigorous quantitative research and evaluation projects across multiple Learning Supports initiatives.
• Apply appropriate quantitative methods to collect, manage, analyze, and interpret data, including leading inferential analyses for both causal and non‑causal research questions.
• Develop, maintain, and document reproducible and collaborative analytic workflows, including data management processes and quality control procedures.
• Review, quality‑check, and strengthen analytic code and outputs produced by junior staff; provide guidance and mentorship to promote best practices in analysis and documentation.
• Translate complex analytic findings into clear, actionable insights for client reports, technical memos, presentations, and briefings.
• Manage discrete project tasks or analytic components, including planning timelines, tracking deliverables, and coordinating with project leadership and clients.
• Support proposal development by contributing to technical and analytic sections and helping shape study design and analytic approaches.
• Engage with internal and external stakeholders through meetings and dissemination activities, contributing to a collaborative and inclusive team environment.

Qualifications

Education, Knowledge, and Experience

• A Master’s degree with 4 years of relevant quantitative research experience or a Bachelor’s Degree with 5 years of relevant experience.
• Demonstrated experience supporting or leading quantitative research or evaluation projects, preferably for public-sector, nonprofit, or education-focused clients.
• Experience designing and executing inferential analyses and contributing to research reports, briefs, or presentations.
• Experience managing and maintaining analytic datasets, including documentation, quality control, and reproducible workflows.
• Experience with machine learning methods or interest in applying ML to support causal and non-causal research preferred, but not required.
• Experience working in education or K–12 research contexts is preferred, but not required.

Skills

• Proficiency in R, Stata, or Python for applied quantitative analysis.
• Ability to review, quality-check, and improve others’ analytic code and support junior staff through guidance and mentorship.
• Strong analytical and problem-solving skills, with attention to accuracy and research best practices.
• Strong communication skills, with the ability to translate complex analyses for technical and non-technical audiences.
• Ability to manage multiple tasks and deadlines independently while contributing to a collaborative team environment.

Disclosures: Applicants must be currently authorized to work in the U.S. on a full-time basis. Employment-based visa sponsorship (including H-1B sponsorship) is not available for this po Apply tot his job Apply To this Job