Associate Data Scientist

Posted 4 Hours Ago
Cambridge, MA, USA
In-Office
Entry level
Edtech
The Role
Perform reproducible analyses on large administrative datasets, build and validate statistical and econometric models for causal inference and forecasting, translate results into dashboards and reports, and document methods while ensuring privacy and data governance compliance.
Summary Generated by Built In
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 Faculty of Arts and Sciences?

The Faculty of Arts and Sciences (FAS) is the historic heart of Harvard University. It is the home of Harvard’s undergraduate program (Harvard College, founded in 1636) as well as all of Harvard’s Ph.D. programs (the Harvard Kenneth C. Griffin Graduate School of Arts and Sciences, founded in 1872), Harvard Athletics and the Division of Continuing Education. The 40 academic departments and 30+ centers of the FAS support a community unparalleled in its academic excellence across the broadest range of liberal arts and sciences disciplines. Together, the FAS seeks to foster an environment of ambition, curiosity and shared commitment to knowledge and truth that elicits excellence from all members of our community and prepares the next generation of leaders through a transformative educational experience.

Job Description

Job Summary:

The Associate Data Scientist will work closely with Opportunity Insights’ Founding Director, Executive Director, faculty, and senior researchers and staff to transform large administrative and program datasets into reproducible analyses, statistical models, and decision-support tools. The position helps translate complex research findings into accessible metrics, visualizations, and reports for internal leadership and external partners, including policymakers and practitioners. This position will report to Raj Chetty, Opportunity Insights’s Founding Director.

Job-Specific Responsibilities:

  • Analyze large, complex administrative and program datasets in support of specific research projects, and contribute to the design, development, and enhancement of OI’s broader data infrastructure.
  • Construct robust statistical models to produce statistics, such as those in the Opportunity Atlas, from confidential microdata, ensuring the application of appropriate privacy protection principles and compliance with data governance standards.
  • Apply advanced statistical and econometric techniques for causal inference, including matching estimators and quasi-experimental designs, to rigorously evaluate program impacts and economic mobility outcomes.
  • Build, calibrate, and validate models for financial forecasting, social impacts, and other economic and social benefits, including demand estimation and policy impact analysis, to inform data-driven decision-making.
  • Integrate analytical findings into well-structured dashboards, reports, and visualizations for internal decision-makers and external partners, ensuring clarity, accessibility, and alignment with stakeholder needs.
  • Document methodologies, data transformations, and analytical workflows in a clear and reproducible manner, supporting transparency, knowledge transfer, and long-term maintainability of OI’s analytical assets.

Working Conditions:

This position will be based in Cambridge, MA. The work is mainly performed in an office setting. Flexible work options for this role will be discussed during the interview process.  

Physical Requirements:

Applicants must be able to perform typical office tasks, including sitting for extended periods, using standard office equipment, and occasionally lifting up to 20 pounds.

Qualifications

Basic Qualifications:

  • Bachelor’s Degree in Statistics, Data Science, Computer Science, Economics, Econometrics or a related field.

Additional Qualifications and Skills:

  • Experience with data analysis, economics research, or econometrics
  • Proficiency in Python and languages such as Stata or R for data analysis
  • Experience with creation and analysis of large datasets
  • Familiarity with modern AI coding tools (e.g., Claude Code)
  • Experience and interest in working in collaborative settings with other team members

Additional Information

  • Appointment End Date: Two years from date of hire (with the possibility of renewal)
  • Standard Hours/Schedule: 40 hours per week
  • Visa Sponsorship Information: Harvard University is unable to provide visa sponsorship for this position
  • Pre-Employment Screening: Identity, Education

Other Information:

  • Two-year term position with possibility of renewal.
  • A cover letter is highly encouraged for consideration.
  • All final offers will be made by FAS HR.

Opportunity Inisghts is a non-partisan, not-for-profit organization based at Harvard University and directed by Raj Chetty, John Friedman, and Nathaniel Hendren. We conduct scientific research using “big data” on how to improve upward mobility and work collaboratively with local stakeholders to translate these research findings into policy change. We also train the next generation of social scientists and practitioners to improve opportunity for all.

Work Format Details

This position has been determined by school or unit leaders that all duties and responsibilities must be performed at a Harvard or Harvard-designated location. Certain visa types may limit work location. Individuals must meet work location sponsorship requirements prior to employment.

Salary Grade and Ranges

This position is salary grade level 056. 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.

Skills Required

  • Bachelor's Degree in Statistics, Data Science, Computer Science, Economics, Econometrics or related field
  • Experience with data analysis, economics research, or econometrics
  • Proficiency in Python
  • Experience with Stata or R
  • Experience creating and analyzing large datasets
  • Familiarity with modern AI coding tools (e.g., Claude Code)
  • Experience applying privacy protection principles and complying with data governance for confidential microdata
  • Ability to document methodologies, data transformations, and reproducible analytical workflows
  • Experience and interest in collaborative team-based research settings

Harvard Business School Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Harvard Business School and has not been reviewed or approved by Harvard Business School.

  • Leave & Time Off Breadth Time off is considered broad, covering vacation, sick and personal days, numerous paid holidays including a winter recess, and paid parental leave. This breadth is positioned as a core part of the total rewards package.
  • Healthcare Strength Health coverage includes multiple medical plan options alongside dental, vision, FSAs/HSAs, and specialized support for high medical costs. This range of options is framed as competitive with large private employers.
  • Retirement Support Retirement programs include a university tax‑deferred 403(b) with automatic enrollment and escalation plus additional pension/retirement programs for eligible groups. These features are presented as part of a strong long‑term financial benefits offering.

Harvard Business School Insights

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The Company
HQ: Boston, MA
Year Founded: 1908

What We Do

Founded in 1908 as part of Harvard University, Harvard Business School is located on a 40-acre campus in Boston. Its faculty of more than 250 offers full-time programs leading to the MBA and PhD degrees, as well as more than 175 Executive Education programs, and Harvard Business School Online, the School’s digital learning platform. For more than a century, faculty have drawn on their research, their experience in working with organizations worldwide, and their passion for teaching, to educate leaders who make a difference in the world. The School and its curriculum attract the boldest thinkers and the most collaborative learners who will go on to shape the practice of business and entrepreneurship around the globe. Community Guidelines: We may hide or block persons or hide or delete comments that include obscenities or are explicit, are spam or duplicate posts, spread misinformation, are irrelevant to the post, or are otherwise deemed inappropriate.

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