"Data Scientist"

Job Summary

Provide leadership in advocating for and expanding the use of data analytics; lead a variety of projects, data consulting, and quantitative analysis services to a broad range of clients. Support strategic objectives based on an informed, fact-based, and analytical understanding. Focus on big-picture and strategic issues; develop policy. Projects are large, complex, and multi-faceted.

Job-Specific Responsibilities

The Data Scientist will have two responsibilities. The first is to conduct economic and statistical analysis to support evidence-based investments and cost-benefit evaluation to promote economic mobility. The person in this role will design and implement statistical and econometric models to estimate program impacts, develop financial models of returns to program investments, and conduct cost-benefit and impact analyses. The second objective is to translate findings from these analyses and other ongoing research at Opportunity Insights into actionable insights for external stakeholders and the broader public, ranging from policymakers to students participating in OI’s new data science courses. Both sets of activities will be conducted in collaboration with other current members of the Opportunity Insights team.

The individual taking on this role will be responsible for the following:

Policy Evaluation and Financial Modeling

• Lead efforts to acquire, clean, and manage large administrative and program datasets.
• Design and conduct econometric studies assessing the effectiveness of public policies, social programs, and other mobility-related interventions.
• Apply causal inference methods including matching estimators, quasi-experimental designs, and other techniques.
• Model financial returns from alternative portfolios of investments, including expected returns and risk assessment.
• Ensure methodological rigor and transparency in all analyses.

Cost-Benefit Analysis and Tool Development

• Conduct cost-benefit analyses (CBA) to estimate returns of programs.
• Quantify direct and indirect economic and social benefits.
• Develop a calculator to estimate cost savings and impacts of state and federal tax revenues.
• Integrate findings into dashboards, reports, and visualizations for internal decision-makers and external partners.

Teaching and Mentoring

• Support OI initiatives to teach data science and OI research to high school and college students.
• Supervise and collaborate with junior analysts and predoctoral research assistants as needed.
• Provide technical guidance on modeling, interpretation, and quality assurance.
• Contribute to internal capacity building and knowledge-sharing across teams.

Communication of Results

• Produce technical reports summarizing results for relevant internal and external stakeholders.
• Help prepare non-technical policy briefs, reports, and presentations summarizing key findings, uncertainties, and implications.
• Represent the organization in briefings, conferences, and stakeholder meetings.

Working Conditions

The position is located in Cambridge, MA, with the possibility of hybrid work arrangements.

Qualifications

Basic Qualifications

• Minimum of seven years’ post-secondary education or relevant work experience
• Supervisory experience

Additional Qualifications and Skills

• Ph.D. in Economics, Public Policy, Statistics, or related field.
• Minimum 2 years of professional experience in applied econometric analysis, preferably in policy evaluation, government, or academic settings.
• Expertise in:
  • Causal inference and econometric modeling
  • Analysis of big data
  • Cost-benefit analysis
  • Quantitative impact evaluation and forecasting
  • Writing technical and non-technical economics papers
  • Programming languages such as R, Stata, Python, and SAS
• Proven ability to translate technical results into actionable policy insights.
• Excellent written and verbal communication skills, including experience presenting to non-technical audiences.
• Experience and interest in working in collaborative settings with other team members.

Additional Information

• Standard Hours/Schedule: 35 hours per week
• Visa Sponsorship Information: Harvard University is unable to provide visa sponsorship for this position
• Pre-Employment Screening: Identity
• Other Information: This is a 12-month term position with a strong possibility of renewal. To be considered for this position, a cover letter and resume/CV must be submitted. A skills assessment may be required as part of the interview process.

Opportunity Insights (OI) is a nonpartisan research and policy institute focused on improving economic opportunity. Founded in 2018, Opportunity Insight has become a nationally- and internationally- recognized leader in the science of economic mobility and in the use of large administrative data to understand and address inequality. Opportunity Insights has published seminal work on national trends in upward mobility; racial disparities; the role of neighborhoods, social capital, and higher education in upward mobility; and the use of private-sector data to understand disparate impacts in the recent economic recession and recovery. To complement this research, Opportunity Insights has developed data resources including the Opportunity Atlas, the Social Capital Atlas, and the Economic Tracker to support evidence-based policy and practice. To date, OI’s work has shaped policy discussions at the national and local level, with nearly a dozen of its studies covered on the front pages of major media outlets, such as the New York Times, The Economist, the Wall Street Journal, and have been widely cited in policy discussions, including the President’s State of the Union address.

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 059. 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.