Quant Guide 2020: Georgia Institute of Technology

Atlanta, US

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The Master of Science in Quantitative and Computational Finance at Georgia Institute of Technology – commonly referred to as Georgia Tech – is one of the highest-ranking new entrants in this year’s Risk.net quant guide, debuting at number 13. It is assisted by a 100% graduate employment rate, and an average starting salary of $93,105.

The 1.5 year, three-semester programme is led by Sudheer Chava, professor of finance. It is one of a group of programmes run on a collaborative basis by a number of the institution’s departments. In Georgia Tech’s case, those departments are the Scheller College of Business, the H Milton Stewart School of Industrial and Systems Engineering and the College of Sciences, with some additional classes delivered at the College of Computing.

According to Chava, the degree prepares students for the big shifts taking place in the financial industries. The curriculum began to focus on data analysis and machine learning in 2014 – “both on the underlying fundamentals of machine learning algorithms and the applications of machine learning to various financial applications. The focus on data science has been steadily increasing every year,” he says.

Alongside growth in demand for skills of this sort within the industry, Chava has observed shifting career paths among graduates of the programme. “There was an increased demand for risk management and model validation jobs after the 2008 crisis,” Chava says. “For the past few years, we are seeing an increase in fintech and data scientist jobs.”

All students take a set of six mandatory courses, as well as a project-based course, involving presentations of papers and methodologies; a group of targeted electives, in which students choose two of three; and a series of free electives – a large number of degree-relevant classes drawn from across the contributing departments.

View other universities and a guide to the metrics tables

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