Current Columbia undergraduate students from Columbia College, SEAS, School of General Studies, and Barnard are offered the opportunity to earn both the bachelor’s degree and the master’s degree (BA/MA) in a shorter period of time thus, making it more financially advantageous. The BA/MA in Statistics is open to students from all majors.
Qualifying students typically apply to the program during their junior year or the first semester of their senior year. In the graduate portion of the program, admitted students can be hired as RAs or Graders in their first semester and save on the tuition cost of .5 RU. We also offer a small number of BA/MA summer bridge research internships. The program is ideal for students whose career goals will be furthered by graduate-level training and who are planning to pursue a Ph.D. in statistics or another field.
Only upon enrollment in the Graduate School of Arts & Sciences (GSAS) can a BA/MA student receive transfer credit for up to three courses (9-12 credits) and up to 0.50 RU for graduate courses (4000-level and above) taken in excess of the 124-credit requirement for the Columbia or Barnard bachelor’s degree (i.e., courses that did not count toward the undergraduate major, concentration, or general education requirements).
Applicants interested in the BA/MA option should apply at least two months prior to the semester in which they intend to begin taking courses that will count towards the MA. The GRE is optional but not required to apply. For application instructions and details visit our Application Procedures. The application deadline for 2022 is now open.
- Applicants who wish to begin taking courses for graduate credit during the Spring 2022 semester must submit the BA/MA application by November 16, 2021.
- Applicants who wish to begin taking courses for graduate credit during the Fall 2022 semester must submit the BA/MA application by April 22, 2022.
Director, Data Science 2U
Current Title: Director, Data Science, 2U
- Got to live out one of my dreams and work for a Major League Baseball team when I interned for the New York Yankees as statistical analyst for a year.
- While working at TheLadders, I had the privilege of mentoring a summer intern. I felt tremendous satisfaction from seeing him learn and grow, and loved passing some of my knowledge and experience on to him.
- After working with product managers and software engineers on a new website feature for many months, it felt great to finally roll it out to our users and to see how much it improved their experience.
“At Columbia, I learned both the theories and the practical skills that I needed to find a great job and start contributing immediately, and which I continue to use me to this day.”
Role: Portfolio Manager, Cable Car Capital LLC
Jacob completed the MA program along with a BA in Comparative Literature & Society from the College and was a Teaching Assistant in the department.
- After graduation, Jacob worked in financial analyst roles at McKinsey and two fundamentally-oriented investment firms, where he used econometric modeling and time series analysis techniques in several research projects.
- In 2013, he founded Cable Car Capital LLC, an investment adviser that manages a long/short equity hedge fund.
- While some investment strategies require applied statistical analysis, Jacob notes that his research is now more qualitative.
"Coursework on quantitative methods in finance helped narrow my investment-related career interests. While I decided against becoming a quant, the MA program gave me a great foundation for thinking about the world in probabilistic terms, which is core to my role as a portfolio manager."
Chris Mulligan, Dual Degree BA/MA in Statistics, 2015
Role: Quantitative Researcher, Two Sigma Investments LP
- Current duties: build statistical models to make financial market predictions using highly non-traditional data.
"The Statistics department provided a grounding in the key areas of statistics, giving me a set of tools I've been able to directly leverage professionally. More importantly, the department taught me how to learn and understand statistical problems, so that when I face novel problems in the future I can figure out how to solve them."