Data Scientist, M-Powering Teacher Coaching

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 relevant experience and interest in the position.
• All candidates invited to the in-person/hybrid interview may be asked to complete a task and/or submit a sample program.

This is a full-time, one-year term appointment beginning on the date of hire, with the possibility of continuation based on funding, performance, and departmental needs.

The work arrangement is remote, subject to project and departmental needs.

Additional Qualifications and Skills:

• 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.

• Appointment End Date: One year from date of hire
• Standard Hours/Schedule: 35 hours per week
• Compensation Range/Rate (including Shift Differential if applicable): $90,000 - $95,000 commensurate with experience
• Visa Sponsorship Information: Harvard University is unable to provide visa sponsorship for this position
• Pre-Employment Screening: Identity and Education

Work Format Details

This position has been determined by school or unit leaders that the duties and responsibilities can effectively be performed fully remotely at a non-Harvard location. Employees in fully remote positions must work all scheduled hours in a Harvard registered state in compliance with the University’s Policy on Employment Outside of Massachusetts. At the discretion of the department, fully remote employees may occasionally be required on site at a Harvard location. Certain visa types and funding sources may limit work location. Individuals must meet work location sponsorship requirements prior to employment.

Salary Grade and Ranges

This position is salary grade level 057. Please visit Harvard's Salary Ranges to view the corresponding salary range and related information.

Benefits

Harvard offers a comprehensive benefits package that is designed to support a healthy work-life balance and your physical, mental and financial wellbeing. Because here, you are what matters. Our benefits include, but are not limited to:

• 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

Learn more about these and additional benefits on our Benefits & Wellbeing Page.

EEO/Non-Discrimination Commitment Statement

Harvard University is committed to equal opportunity and non-discrimination. We seek talent from all parts of society and the world, and we strive to ensure everyone at Harvard thrives. Our differences help our community advance Harvard's academic purposes.

Harvard has an equal employment opportunity policy that outlines our commitment to prohibiting discrimination on the basis of race, ethnicity, color, national origin, sex, sexual orientation, gender identity, veteran status, religion, disability, or any other characteristic protected by law or identified in the university's non-discrimination policy. Harvard's equal employment opportunity policy and non-discrimination policy help all community members participate fully in work and campus life free from harassment and discrimination.