Data Scientist, M-Powering Teacher Coaching
About The Position
At the Center for Education Policy Research at Harvard University (CEPR), the mission is to transform education through the power of quality evidence. The Math Teaching and Teacher Learning team at CEPR provides math-specific professional development to teachers and coaches to help improve math instruction. Current grant-funded projects aim to develop and test an expanded math-specific coach training program (M-Powering Teacher Coaching) that utilizes machine-learning automated feedback and AI-enhanced coaching tools. The Data Scientist will contribute to this and other projects that bridge rigorous educational research with practical tools for teachers, instructional coaches, and education leaders. This role involves overseeing, managing, and leading the analysis and application of complex datasets, and contributing to the integration of research insights into innovative educational tools and cutting-edge products. The Data Scientist will join a team led by faculty lead and Principal Investigator, Heather Hill, and will collaborate with researchers from higher education institutions, professional learning organizations, curriculum providers, and Enterprise AI firm(s).
Requirements
- 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.
- 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.
Nice To Haves
- Master’s degree in data science, statistics, computer science, education, economics, social science, or a related field preferred.
- Experience with R, Python, Stata, or a similar programming language preferred.
- Experience with machine learning, natural language processing, generative AI, or automated scoring strongly preferred.
- Experience with data annotation, codebook development, or qualitative and quantitative coding preferred.
- Familiarity with building reproducible workflows for data cleaning, processing, analysis, or modeling preferred.
- Familiarity with version control, databases, APIs, or collaborative software development preferred.
- Experience with K-12 education data or education research is a plus.
- Experience with mathematics teaching and learning is a plus.
- Interest in improving education through responsible and evidence-based uses of artificial intelligence; commitment to equity, diversity, inclusion, and belonging.
Responsibilities
- 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.
- Conducts 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.
- 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).
- 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.
Benefits
- Generous paid time off including parental leave
- Medical, dental, and vision health insurance coverage starting on day one
- Retirement plans with university contributions
- Wellbeing and mental health resources
- Support for families and caregivers
- Professional development opportunities including tuition assistance and reimbursement
- Commuter benefits, discounts and campus perks
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What This Job Offers
Job Type
Full-time
Career Level
Entry Level
