What You'll Learn
a fully integrated, interdisciplinary approach to quantitative finance
The Master of Science in Computational Finance (MSCF) curriculum was developed from the joint venture between four Carnegie Mellon University colleges. This unique collaboration enables MSCF to offer a tight integration of statistics, computer science, mathematics and finance - the four disciplines underlying computational finance.
MSCF’s reputation for excellence lies squarely on the strength of our faculty and the custom-tailored courses developed and updated over the past twenty-seven years. Well-balanced between theory and practice, MSCF offers a blend of carefully coordinated quant, applied finance and computational coursework. It is the best of its kind.
While students are permitted a degree of specialization in the last two mini-semesters through their choice of electives, the program is largely fixed with each set of courses preparing the groundwork for the next, more advanced, set. With all our students taking the same set of core courses, recruiters value our students’ consistent ability to meet the analytical and technical challenges facing the industry.
Students in the MSCF program are exposed to a wealth of experiential learning opportunities to supplement the core curriculum. These initiatives will help you convert theory into practice and gain “real-world” experience required by top employers.
One of the following 12-unit courses can be taken to replace 12 units of MSCF electives as an approved substitute. Students can also request that other CMU courses be used as approved substitutes. These requests must be approved by the designated Steering Committee member to count as approved substitutes.
Students should note that CMU Elective courses are not taught by the MSCF program, and are not under the program's control and (1) may not be offered in a remote format, making them unavailable to students at the New York City location; (2) are subject to enrollment limits that may preclude MSCF students from taking them; (3) could be unavailable because of a schedule conflict with required MSCF courses; (4) will conform to the standard University calendar which can differ from the MSCF calendar, especially around the times of final exams; (5) must be taken for a letter grade.
Approved Substitute CMU Electives:
- 10-605, Machine Learning with Large Datasets
- 10-703, Deep Reinforcement Learning and Control
- 11-611, Natural Language Processing
- 11-785, Introduction to Deep Learning
Understanding the robust market information provided through the Bloomberg terminals is vital for success in the quant finance industry. The Bloomberg Market Concepts certification prepares you for your internship and helps translate your classroom learning to the real-world.
The summer internship provides an opportunity to experience the inner workings of the financial markets and apply the skills learned in your first year of the program. Recruiter interest in our students is strong and our career counselors will work closely with you to assist you in the internship search.
Studies in Financial Engineering
This second-year course focuses on solving risk management and trading problems and the process for selling derivative deals. The highlight of the MSCF Studies in Financial Engineering is a series of in-class team case presentations for practicing client pitches on complicated financial products.
Focused exclusively on data science and machine learning, the MSCF Capstone builds on the five-course data science curriculum during the first year of the program. As a second-year MSCF student, you will implement various data and statistical methods to address a real-world challenge at a financial firm.
Joining the MSCF Trading Club will give you access to up-to-date financial market knowledge and the opportunity to participate in a series of financial market seminars and simulated trading sessions. For more information, visit our Student Experience page.
MSCF Speaker Series
The MSCF Speaker Series features presentations from industry practitioners on various quant finance topics including applications, products, and market challenges. It is an invaluable opportunity to gain first-hand industry knowledge and learn about unique experiences and perspectives from quant finance veterans.