Insights into Master of Science in Computational Finance (MSCF) & its Career Prospects

A close look at the course curriculum and our vast experience in counselling students for various professional programs in India and Abroad suggest that Computational Finance is the other name of Financial Engineering, which is an interdisciplinary field that applies mathematical practice and methods to provide solutions in finance. Higher Education Institutes have several names for these programs, including Financial Engineering, Financial Mathematics, Mathematical Engineering, and Computational Finance. These programs are housed in departments such as Mathematics, Engineering, Finance and Business Studies. Graduates often find employment in promising fields of Investment Banking, Business, Regulatory Agencies and Insurance Companies.

MSCF program was formed at Carnegie Mellon University with the collaboration of four departments – Department of Statistics in Dietrich College of Humanities and Social Sciences, Heinz College School of Information Systems and Management, Mathematical Sciences Department in the Mellon College of Science and Tepper School of Business. The participation of four departments enables the program to shift emphasis as the needs of the industry change.

MSCF’s highly-integrated, interdisciplinary curriculum is made possible only by this joint venture and is the key to their success. Programs owned by business schools can be strong on financial markets but pay less attention to mathematical modelling. On the other hand, programs owned by math departments are often highly theoretical and less focused on “real world” applicability. The key feature is that this curriculum is well-balanced between theory and practice. Programming is deeply embedded into the curriculum, an important skill in today’s increasingly technical financial markets.

Career Path:  Over the last two decades, increased competition, advances in technology and the globalization of markets have dramatically lowered the cost and increased the speed and volume of data available for decision-making. Extensive regulation, implemented after the 2008 financial crisis, requires financial firms to better measure and control risk in their portfolios.

To succeed, bankers, traders and money managers must understand the proper use and limitations of the mathematical models on which their decision-making is based, the statistical analysis and probabilistic distributions driving economic forecasts and the management of software development necessary to implement these tools. The students of MSCF are trained to meet these industry needs.

While the graduates take varied positions in quantitative finance, the four careers paths most frequently pursued are: Sales & Trading, Financial Modeling/Strategies/Research, Quantitative Portfolio Management and Risk Management.

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