Course Overview

The Computational Finance program at Carnegie Mellon University is a pioneering interdisciplinary degree that combines expertise in mathematics, computer science, and finance. Offered through a collaboration between multiple departments, including the Tepper School of Business and the Department of Mathematical Sciences, the program aims to equip students with advanced quantitative skills to address complex challenges in financial markets. Unique features include a rigorous curriculum focused on financial modeling, algorithmic trading, and risk management, alongside hands-on experience with cutting-edge computational tools.

Career Prospects

Graduates of this program are highly sought after in the finance industry, with strong prospects in roles that require expertise in quantitative analysis and technology. The program’s emphasis on practical skills ensures alumni are well-prepared for dynamic careers in investment banking, asset management, and fintech.

Key Faculty and Staff

The program is supported by distinguished faculty from the Tepper School of Business and the Department of Mathematical Sciences, known for their research in financial mathematics and computational methods. Specific faculty names and roles are available on the university’s official program page.

Unique Facilities and Partnerships

Students benefit from access to state-of-the-art computational labs and financial data platforms at Carnegie Mellon. The university maintains strong industry connections, offering networking opportunities and internships with leading financial institutions in the United States.