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MS Overview

Graduates of the MS&E program know math, engineering and behavioral science. They can conduct experiments to design better systems, organizations, and work processes. They understand how to analyze data to solve real-world problems, and develop mathematical and computational models to inform action. They know how to surface and examine unarticulated assumptions and root causes. They can communicate effectively in the team environments found in so many contemporary organizations.

Area of Specialty

1. Financial Analytics

Students who concentrate in Financial Analytics are prepared for careers that require analytical rigor and the ability to innovate around market challenges. Example career paths include financial services, risk management, investment management, financial technology and data processing, financial regulation and policy, exchanges and clearinghouses, and auditing and compliance. The concentration combines the in-depth study of quantitative techniques with practical, hands-on business problem solving. Students learn to use mathematical models and quantitative tools to solve complex problems in finance practice. The concentration exploits the intellectual ties between finance, operations research, computer science, and engineering. It offers a high level of flexibility and a range of elective courses that allow students to tailor the program to their specific career goals. Required courses immerse students in quantitative methods and deepen their understanding of finance fundamentals. Projects courses feature practical, data-driven team projects and case studies to foster group learning and interaction with peers.

2. Operations and Analytics

The Operations and Analytics track prepares students in the fundamentals and applications that are critical to careers in fields ranging from operations management in the service, healthcare, production, manufacturing, computer, telecommunications, and banking industries, to modern Silicon Valley information technology and data analytics. The program emphasizes a balance between the technical rigor of methodologies with lasting value and insightful modern applications and design challenges in a variety of established and emerging industries and operations environments. It offers a portfolio of courses in probabilistic modeling, optimization, simulation, algorithms, data science, networks, markets, and their corresponding applications.

3. Technology and Engineering Management

Students who concentrate in Technology and Engineering Management are prepared for careers including product and project management, management consulting, and entrepreneurship. They acquire skills to manage technical organizations, foster innovation, and deal with rapidly evolving technologies and dynamic markets. Specialized coursework is flexible, allowing students to explore and gain depth and understanding of technical organizations to develop a culture of successful innovation and entrepreneurship, along with methods for decision making under uncertainty, financial analysis, and strategic planning.

4. Computational Social Science

The Computational Social Science track teaches students how to apply rigorous statistical and computational methods to address problems in economics, sociology, political science, and beyond. The program prepares students for a diverse set of career paths in data science, information technology, and policy analysis. The core coursework covers fundamental statistical concepts, large-scale computation, and network analysis. Through electives, students can explore topics such as experimental design, algorithmic economics, and machine learning.

5. Decision Analysis and Risk Analysis

Students who specialize in Decision and Risk Analysis are prepared for careers including management consulting, policy analysis, and risk management, applying engineering systems analysis to tackle complex economic and technical management problems in the private and public sectors. They acquire the skills to identify and develop opportunities in uncertain situations while recognizing and hedging the downside risks. Specialized course work includes the mathematical foundations for modeling in dynamic uncertain environments to value and manage uncertain opportunities and risks, applications to public policy, and an opportunity to work on a client project under faculty guidance.

6. Energy and Environment

The Energy and Environment track is designed for students interested in energy and environmental issues from the perspectives of public policy, non-governmental organizations, or corporations. This track includes core courses in economic analysis, energy resources, and energy/environmental policy analysis; and an individually designed concentration, typically emphasizing policy, strategy, or technology. Seminars provide insights into current corporate strategy, public policy, and research community developments. Energy/environmental project courses give practice in applying methodologies and concepts.

7. Health Systems Modeling

The Health Systems Modeling track is designed for students interested in healthcare operations and policy. The courses in this track emphasize the application of mathematical and economic analysis to problems in public health policy and the design and operation of healthcare services.

Background Requirements

Students are expected to have completed both MATH 51 Linear Algebra and Differential Calculus of Several Variables, or an equivalent multivariable differential calculus course, and CS 106A Programming Methodology, or an equivalent general programming course, before beginning graduate study. These courses do not count toward degree requirements.

Degree Requirements

The MS&E Master's section of the University Bulletin details the MS&E MS degree requirements. All programs represent substantial progress in the major field beyond the bachelor’s degree.

Most students complete the program in five academic quarters, working at an internship in the summer quarter, for a total of 18 months. The MS can, however, be earned in one academic year (three academic quarters) of full-time work.

Students must take a minimum of 45 course units as follows:

— Three core courses (9-12 units)

— A primary or specialized concentration (12-24 units)

— One project course or two integrated project courses (0-8 units)

— Elective courses (1-24 units; see restrictions in the Bulletin)

University Requirements and Resources

University Bulletin
Details university requirements for the master's degree.

GAP Handbook
Graduate Academic Policies and Procedures handbook (the GAP handbook) is a compilation of university policies and other information related to the academic progress of Stanford graduate students from their application and admission to the conferral of degrees and retention of records.

Guide for New Graduate Students
Information for newly admitted graduate students on financing graduate study, registration, health requirements, housing, and visas for international students.