Overview:
The City of Boston is expanding access to Generative AI tools and training for City employees. The Department of Innovation and Technology (DoIT) is seeking a part-time Generative AI Research and Evaluation Fellow to support this initiative by providing research support and assisting with training sessions for City employees.
This part-time fellowship is structured like an applied research assistantship. The Fellow will support the design of evaluations, survey-based measurement, recurring adoption reporting, and analytic write-ups used by program leadership. The Fellow will work closely with the Director of Research and Evaluation and other stakeholders to support the rollout and training efforts.
Responsibilities:
- Support survey design, operations, and data management.
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Write and maintain SQL queries; clean, validate, document, and join data from multiple sources using R for adoption tracking and evaluation.
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Produce analytic outputs for internal decision-making, including tables, charts, summary metrics, and appendix-style materials.
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Support evaluation methodology and internal communications by drafting memos, documentation, and participating in regular check-ins and working sessions.
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Support training sessions for City employees and assist in developing related training materials.
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Performs other related duties as required.
Professional Development and Supervision:
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The Fellow will receive close supervision from the Director of Research and Evaluation, including regular check-ins, feedback on analytic work products, and guidance on research documentation and internal writing.
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Work closely with staff across multiple City departments, gaining exposure to cross-departmental collaboration and applied policy work.
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The role provides exposure to applied evaluation work in government, including survey operations, rollout measurement, and communicating results to decision-makers.
Minimum Entrance Qualifications:
- A bachelor's degree in economics, political science, public policy, urban planning, or a related field is preferred.
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Experience writing SQL for analysis.
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Experience cleaning and analyzing real-world datasets using R.
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Familiarity with survey-based data and basic survey operations (SurveyCTO is preferred).
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Understanding of evaluation or applied research methods, with interest in experimental or quasi-experimental work.
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Strong writing skills and the ability to communicate clearly with technical and non-technical audiences.
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Interest in public service and using data to improve City operations and resident outcomes.
BOSTON RESIDENCY REQUIRED
Terms:
Union/Salary Plan/Grade: Non-Union / $25 per hour
Hours per week: 14