The Financial Data Science and Risk Management (FSRM) Program at Rutgers University offers a 30-credit Master’s degree in Statistics focused on the analysis and modeling of financial data and risk management. Students in this STEM-designated program receive core training in probability theory, statistical inference and advanced statistical and computational methods tailored to financial data analysis and modeling and risk management. They also receive supportive education in related financial concepts and market structure, operations, trading instruments and risk-related regulation.
Courses are taught by a faculty of experts in the mathematics of uncertainty and in statistical modeling and data analysis. Industry practitioners also contribute to instruction and training through workshops and seminars. Students benefit from a dynamic learning environment featuring internships, projects and case study assignments using real financial data, as well as attendance at practitioner seminars, industry events, career development workshops and mentorship opportunities. By bringing together a world-class faculty, Advisory Board and university located close to New York City, the FSRM program prepares students for a wide range of careers in the financial industry.
A Unique Proposition
Traditional quantitative finance programs focus primarily on mathematical modeling for developing and pricing complex derivative products. Although fundamental financial engineering concepts, such as no-arbitrage pricing, risk-neutral valuation and stochastic calculus are a component of the FSRM Program, we are unique in emphasizing statistical tools and data analytics for measuring, monitoring, managing and mitigating uncertainty, risk and volatility. Students do an in-depth studies of important topics such as advanced applied parametric and non-parametric statistical methods in finance; advanced time series analysis applied to financial and economic data and forecasting; multivariable regression analysis, data mining, data visualization and predictive analytics; algorithmic trading and portfolio management, statistical modeling of default probabilities, losses given default and exposures at default; scenario analysis and stress testing; event driven loss distributions for operational risk management and many other statistically driven topics as applied to financial data and risk management.
Our commitment is to ensure students are equipped to solve the complex problems financial institutions face today. We recognize that the standard assumptions or “stylized facts” of finance do not always apply in a real world situation. Students are taught to statistically examine and analyze the data for deviations from expected behavior and to use robust methods to mitigate and manage their impact.
The FSRM program has qualified for academic partner status with the leading industry risk management associations, GARP and PRMIA.
Our Advisory Board
Our Advisory Board comprises senior executives from major financial institutions as well as academicians. Through semi-annual meetings and reviews, these leading practitioners and academics provide valuable feedback, ensuring the content of the FSRM program reflects the industry’s changing needs.
Practitioner Seminar and Practitioner as Instructor
The FSRM Practitioner Seminar series held once or twice a month brings leading professionals in finance and risk management to the campus to give talks on the quantitative and statistical aspects of their work and advice to students on managing their careers. Students are required to attend the seminars as part of the practical training component of the program, and they benefit by connecting what they learn in the series with the course content. Examples of past practitioner seminars are posted on this site at
In addition, the Practitioner as Instructor initiative brings practitioners into the classroom to teach selected topics such as regulatory-driven model development and validation and stress testing.
FSRM graduates and students have accepted quantitative, risk and technical positions at ABN Amro, Aflac, AIG, AllianceBernstein, Amazon, Bank of America, Blackrock, Bloomberg LP, Capital One, Cerberus Capital Management, Citibank, CME Group, Deloitte, Deutsche Bank, Discover, Federal Reserve, Genpact, Goldman Sachs, Google, Guggenheim Partners, Harvest Fund Management, HSBC, Imagine Software, Jacobs Levy Equity Management, JP Morgan, KPMG, McKinsey & Company, Met Life, Microsoft, Mizuho Americas, Morgan Stanley, MUFG, Munich Re, Nomura Securities, Pinz Capital, RBC Capital Markets, Santander Bank, Scotiabank, Societe Generale, Sumitomo Mitsui Banking Corp, Transamerica, Valley Bank, Verisk Analytics, Whitebox Advisors and many other companies.
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