Yale’s Computer Science and Economics B.S. is a structured interdepartmental major combining rigorous coursework in algorithms, data structures, and programming with economic theory, econometrics, and applied data analysis. It is ideal for students pursuing careers in tech, analytics, or economic research.
The program balances theoretical foundations with applied problem-solving and equips students to understand how algorithms and incentives co-shape behavior, business, and society.
Core Curriculum Components
Mathematics & Statistics Foundation
MATH 120: Multivariable Calculus
MATH 222 or 225: Linear Algebra or Intensive Linear Algebra
S&DS 241: Probability Theory
S&DS 242: Theory of Statistics or equivalent course in statistical inference
Computer Science Core
CPSC 201: Introduction to Computer Science
CPSC 223: Data Structures and Programming Techniques
CPSC 365: Design and Analysis of Algorithms
CPSC 366 or 440: Machine Learning or Theory of Computation
Economics Core
ECON 110/115: Introductory Microeconomics
ECON 111/116: Introductory Macroeconomics
ECON 121/125: Intermediate Microeconomics
ECON 131/135: Econometrics and Statistical Modeling
ECON 159: Game Theory or ECON 159a: Behavioral Economics (as an elective)
Interdisciplinary & Capstone
Senior Research Project (ECON 491 or CPSC 490): Students complete a substantial independent project that applies both computational and economic principles—such as algorithmic pricing, economic simulations, or ML models of labor markets.
Ethics & Policy Options: Courses such as CPSC 183 (Law, Technology, and Culture) or ECON 465 (Global Economic Policy)
Yale’s interdisciplinary environment encourages CS+Econ students to engage in applied learning through research, internships, and startup development.
Undergraduate Research
Students may join faculty-led research groups at:
Yale Economic Growth Center
Cowles Foundation for Research in Economics
Yale Center for Algorithms and Data Science
Y-RISE (Impact Evaluation Lab)
Digital Ethics Lab (Policy & Regulation Focus)
Research may focus on:
Algorithmic pricing and competition
Inequality and labor market trends
Cryptoeconomics and blockchain design
Political economy and tech platforms
Capstone Projects
Topics often include:
Predictive modeling for economic outcomes
Data-driven analysis of healthcare or education markets
Auction design and simulation
Equity analysis in algorithmic decision systems
Internships
Students land prestigious internships with:
Tech companies (Google, Meta, Palantir, Stripe)
Investment firms (Jane Street, Bridgewater, Citadel)
Public sector (Federal Reserve, IMF, World Bank)
Think tanks and academic labs (J-PAL, Brookings)
Hackathons & Competitions
YHack
Datafest
Economics Policy Simulation Challenges
Quant competitions and algorithmic trading hackathons
Graduates of Yale’s Computer Science and Economics B.S. program are known for their dual fluency in computation and economic reasoning. They are sought after for roles requiring analytical depth, cross-disciplinary insight, and the ability to model behavior using both data and incentives.
Career Progression Examples
Software Engineer → Technical PM → CTO
Data Scientist → Analytics Lead → Head of Data Science
Quant Analyst → Portfolio Manager → Chief Risk Officer
Research Assistant → PhD Candidate → Economic Policy Advisor
Strategy Analyst → FinTech Entrepreneur → CEO
Graduate Study
Many pursue:
PhD in Economics, Public Policy, or Computer Science
Master’s in Data Science or Computational Social Science
JD or MBA with a Tech or Finance Focus
MPP (Public Policy) with a data/economics concentration
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