M.S. Data Science in Finance Program

The goal of the program is to equip students with the tools necessary to pursue a career in a quantitative financial field. The 2-year course work provides students with comprehensive and practical knowledge of the mathematical, statistical, and computational skills. The following courses are offered as guides. They should be adapted to suit a student’s needs and an advisory committee’s recommendation. This degree requires 33 credit hours plus an oral final exam. Students in this program are also required to take at least one Data Science in Finance seminar course.

Course Requirements

33 credit hours + DSF seminar (at least once) + oral exam

1. Data Science Foundation (15 credits)

   • STAT 52000

   • STAT 52500

   • STAT 51700 or STAT 52800

   • STAT 51900

   • STAT 52600 or STAT 54500

2. Computational Finance (6 credits)

   • STAT 54000 and STAT 54100

3. Data Science in Finance (6 credits)

   • Machine Learning Finance I (598) and Machine Learning Finance II (598)

4. Electives (6 credits): two courses from the list below

   • STAT 53200

   • STAT 54600

   • Any topic courses 598 or 695

   • CS 54300

   • CS 57300

   • CS 57800

 

Sample Plan of Study

 

1st Fall	STAT 52500	STAT 51900	STAT 54500
Spring	STAT 52600	STAT 52000	STAT 54000
2nd Fall	STAT 54100	STAT 52800	MLF1
Spring	MLF2	Elective1	Elective2