Research Associate, Digital Data Design Institute

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 Harvard Business School?

Harvard Business School, located on a 40-acre campus in Boston, was founded in 1908 as part of Harvard University. It is among the world's most trusted sources of management education and thought leadership. For more than a century, the School's faculty has combined a passion for teaching with rigorous research conducted alongside practitioners at world-leading organizations to educate leaders who make a difference in the world. Through a dynamic ecosystem of research, learning, and entrepreneurship that includes MBA, Doctoral, Executive Education, and Online programs, as well as numerous initiatives, centers, institutes, and labs, Harvard Business School fosters bold new ideas and collaborative learning networks that shape the future of business.

Job Description

Harvard Business School (HBS) seeks multiple Research Associates to support faculty in our Digital Data Design Institute. The successful candidate will have a strong quantitative foundation in data management (both structured and unstructured), machine learning, and statistical modeling to generate research informed insight in support of faculty. This role also involves assisting with field and lab in field studies.

The Research Associate (RA) position reports directly to faculty supervisors and administrative manager in the Research Staff Services office. Ideal RA candidates will be comfortable in an environment that requires a high level of independence, intellectual curiosity, and the ability to use discretionary judgment.

Primary duties

• Build trust and collaboration by being present on-site and engaging directly with colleagues and various constituents.
• Develop and maintain scalable data pipelines for analysis, leveraging machine learning models as well as statistical modeling and causal inference analysis to inform data-driven insights.
• Manage and manipulate data using requested programming, such as R or Python.
• Synthesize research literature in marketing, management science, and organizational behavior to inform empirical work.
• Balance project requests from multiple faculty, using strong communication and prioritization skills. Must be able to structure assignments and keep faculty member informed as necessary, using own judgment.
• Independently manage all timelines and deliverables. Exercise independent decision making with regard to progression of research project and methodologies.
• Responsible for other duties as assigned.

Qualifications

Basic Qualifications

• Bachelor’s degree with a GPA above 3.5 is required.
• Proficiency in R or Python.
• Experience with one of the following required:
  • Programming and Data Handling: Experience with SQL, PySpark, and cloud-based data tools such as Azure Data Lake, Synapse, or Fabric; and strong command of data wrangling, cleaning, and large-scale dataset management.
  • Machine Learning/Deep Learning: Experience with PyTorch, TensorFlow, or Hugging Face; embedding models; and model validation/deployment.
  • Causal Inference/Experimentation: Knowledge of experimental design, randomization, and causal identification methods.

Preferred Qualifications

• Master’s degree in Quantitative Marketing, Management Science, Economics, Data Science, or Computer Science is a plus.
• Experience designing or analyzing field or lab-in-the-field experiments.
• Familiarity with the Microsoft Azure ecosystem, NLP, or AI assistant technologies.

Additional Qualifications:

• Indication of independent research experience and/or applied experience.
• Must be able to take complex research ideas, concepts, and methodologies and apply them to new projects and situations.
• Ability to use own judgement, structure assignments, and keep faculty members informed are a must.
• Excellent communication, interpersonal, organization, research, analytical, writing, and editing skills are required.
• Proven ability to handle multiple projects simultaneously and to adapt to changes in priorities; ability to work calmly under deadline pressure, work both independently and as a team member, take initiative; and follow projects through to completion.
• Strong interest or prior experience leveraging AI.

Candidates with significant advanced experience may be considered at a higher salary grade (56).

Additional Information

Additional Information: This is an immediate hire full-time term position through April 14, 2026, with strong potential for reappointment based on funding and performance.

Standard Hours/Schedule: 40 hours per week

Visa Sponsorship Information: Harvard University is unable to provide visa sponsorship for this position

Pre-Employment Screening: Education, Identity

Other Information: We are reviewing applicants on a rolling basis and encourage applying ASAP for consideration.

This is a hybrid position which we consider to be a combination of remote and onsite work at our Boston, MA based campus. HBS expects all staff to be onsite a minimum of 3 days per week, and departments provide onsite coverage Monday – Friday. Specific hours and days onsite will be determined by business needs and are subject to change with appropriate advanced notice.

We may conduct candidate interviews virtually (phone and/or via Zoom) and/or in-person for this role.

A cover letter, writing sample, and transcripts are required to be considered for this opportunity.

Work Format Details

This position has been determined by school or unit leaders that some of the duties and responsibilities can be effectively performed at a non-Harvard location. The work schedule and location will be set by the department at its discretion and based upon operational needs. When not working at a Harvard or Harvard-designated location, employees in hybrid positions must work in a Harvard registered state in compliance with the University’s Policy on Employment Outside of Massachusetts. Additional details will be discussed during the interview process. 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 055. 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.