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Data Scientist, M-Powering Teacher Coaching

Harvard University · Cambridge, MA · posted 2 weeks ago

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76
Certified filings · by Harvard University, FY2026 Q2
$112,476
Median filed wage · for “Research Scientist” · 3 filings

Source: US DOL Office of Foreign Labor Certification, LCA disclosure data, FY2026 Q2. Government data is published roughly one quarter in arrears.

This advert was matched to Research Scientist, a job title Harvard University has itself sponsored.

The figure above is not this job’s salary. It is what Harvard University reported to the US Department of Labor for the closest role it has sponsored. A filing history means this employer has sponsored before — it is not a promise that this opening carries sponsorship, and not an offer of pay. Check the advert and ask the employer.

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The role, as Harvard University describes it

Job Summary: At the Center for Education Policy Research at Harvard University (CEPR) our mission is to transform education through the power of quality evidence. We believe that if we want to dramatically improve educational outcomes for all children, evidence must play a critical role. The Math Teaching and Teacher Learning team at CEPR provides math-specific professional development to teachers and coaches to help improve math instruction. Our current grant-funded projects seek to develop and test an expanded math-specific coach training program (M-Powering Teacher Coaching) that uses machine-learning automated feedback and AI-enhanced coaching tools. The Data Scientist will contribute to this and other projects that connect rigorous educational research with practical tools for teachers, instructional coaches, and education leaders. This person will oversee, manage, and lead analysis and application of complex datasets, and contribute to the integration of research insights into innovative educational tools and cutting-edge products. They will be joining a team with faculty lead and Principal Investigator, Heather Hill, and collaborators at higher education research institutions, professional learning organizations, curriculum providers, and Enterprise AI firm(s). Job-Specific Responsibilities: Key responsibilities of the Data Scientist include: Data and Research Infrastructure: - Organizes, cleans, and prepares structured and unstructured data (e.g., video, audio, text) for AI modeling and analysis. - Develops and documents codebooks, annotation protocols, data dictionaries, and other research procedures. - Builds and documents reproducible workflows for data processing, annotation, statistical analysis, and modeling. - Supports shared practices for version control, code review, data security, and reproducible research. - Maintains organized project files, code repositories, data documentation, and analytic records. Analysis and Measurement Development - Conduct data science work across grant-funded projects focused on teaching, instructional coaching, curriculum, and artificial intelligence in education. - Applies statistical, machine learning, natural language processing, and generative AI methods as appropriate. - Coordinates and executes the development and evaluation of automated measures related to teaching, coaching, curriculum implementation, and teacher learning. - Supports pilot studies and evaluation activities related to usability, implementation, coaching, and teacher experience. Product Development and Dissemination - Helps integrate research measures and findings into education tools and user interfaces. - Contributes to research papers, reports, public goods, funder deliverables, and other project materials (e.g., tables, figures, visualization, presentations, and technical documentation) Project Management and Cross-team Collaboration - Manages timelines and deliverables across one or more grant-funded workstreams - Collaborates with researchers, educators, software developers, and external partners such as Enterprise AI firm(s) to support project goals. - Oversees internal working groups to deliver on tasks and milestones Performs other duties as assigned.

Basic Qualifications - Bachelor’s degree in Data Science, Statistics, Computer Science, Economics, Mathematics, Education, Social Science, or a related field. - Relevant experience, which may include professional, research, internship, or concurrent-with-baccalaureate experience in data science, statistical programming, machine learning, educational research, or a related field. - Must have strong organizational, communication, and problem-solving skills, with the ability to work independently and collaboratively. - Occasional travel may be required to support project meetings, trainings, pilot activities, or other research-related events. - Candidates should submit a resume or curriculum vitae and cover letter describing their

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