Purdue master's degree features financial problem solving through machine learning

WEST LAFAYETTE, Ind. — Purdue University is offering a new all-online master’s degree in data science in finance with a concentrated curriculum focus on machine learning to solve modern financial problems.

The online degree offers flexibility for working professionals in the financial industry who want to advance their skills and careers, and it makes the Purdue master’s in data science in finance readily available to an international audience of students.

“Purdue’s degree is an interdisciplinary master’s covering topics in data science and finance, but it is the integration of machine learning that sets it apart,” said Kiseop Lee, associate professor of statistics. “Using machine learning, professionals in the financial industry can employ statistical models to draw insights from their data to make strategic decisions, solve financial problems and increase profit.”

Gary Bertoline, senior vice president for Purdue Online and learning innovation, said, “Machine learning is a technique that has become increasingly valued in the financial industry, and emphasizing it in our curriculum puts Purdue’s new master’s degree on the leading edge.”

The innovative two-year program provides learners with comprehensive and practical knowledge of data science and machine learning techniques used by the financial sector to develop investment strategies and manage risk, as well as the mathematical, statistical, and computational skills needed for the creation, implementation, and evaluation of models and products. Graduates will be prepared to move on to or advance in a variety of high-demand, highly technical positions.

The online master’s in data science in finance is a collaboration between the Department of Statistics in Purdue’s College of Science and Purdue’s Krannert School of Management. The program leverages internationally recognized Purdue expertise in data science, machine learning and finance.

Students complete courses in statistics, computational finance, computer science and machine learning. A broad variety of elective courses offered by the Krannert School complements the curriculum with a more general approach to the practices and products of the market. The interdisciplinary program is versatile, allowing students to hone in on subjects of particular interest to them.

The online courses are taught by the same faculty as Purdue’s highly ranked on-campus programs. The curriculum is research-based, emphasizes current best practices and highlights the latest tools, techniques, strategies and processes, including practical skills such as Python programming for machine learning. Lee, whose research focuses on quantitative finance, and statistics Professor Xiao Wang, whose research focuses on artificial intelligence and machine learning, have spearheaded the design and development of the program.

Purdue’s program is designed to qualify students for a wide range of careers both inside and outside the financial industry, including placements at investment banks and trading companies; asset management firms, pension funds and hedge funds; exchanges and clearing houses; insurance companies; energy companies; financial data providers and financial software companies; and ratings and regulatory agencies.

The degree prepares students for jobs as equity trading and sales professionals (quants), financial product designers, financial modelers, financial strategy researchers, investment consultants, quantitative analysts, and risk analysts, among others.

For more information and to enroll in Purdue’s online master’s degree in data science in finance visit the program website.

Writer: Greg Kline, 765-426-8545, gkline@purdue.edu

Sources: Kiseop Lee, kiseop@purdue.edu

Xiao Wang, wangxiao@purdue.edu

Gary Bertoline, bertolig@purdue.edu