Data Scientist, M-Powering Teacher Coaching

Company Description

By working at Harvard University, you join a vibrant community that advances Harvard's world-changing mission in meaningful ways, inspires innovation and collaboration, and builds skills and expertise. We are dedicated to creating a diverse and welcoming environment where everyone can thrive.

Why join the Harvard Graduate School of Education?

The Harvard Graduate School of Education (HGSE) is a diverse community of learners, teachers, and employees who are passionate about changing the world through education and striving for maximum impact in the field of education.

Many choose to work at the Harvard Graduate School of Education because they believe in our mission and are excited by our vision for the future. We have a reputation as a great place to work, for our excellent leadership, and we are a strong community that values diversity. For more information about HGSE, its programs, research, and faculty, please visit (Use the "Apply for this Job" box below)..

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).

Key responsibilities of the Data Scientist include:

• 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.

• 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.

• 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 work streams
• 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…