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Data Scientist, Learning Supports
remoterocketship
- Remote, Oregon, United States
- Remote, Oregon, United States
About
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. Requirements:
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. Benefits:
AIR’s Total Rewards Program is designed to reward our staff competitively and motivate them to achieve our critical mission.
Languages
- English
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