This highly selective program provides twenty interns the opportunity to work with Columbia Business School's faculty on a research project in finance, economics, marketing, management, decision sciences, operations, accounting, or data analytics.  

The work may include literature reviews, data collection and cleaning, web scraping, and statistical analysis. Some projects may require skills in advanced analytics, machine learning, natural langauge processing, and artificial intelligence. Behavioral interns may be staffed on multiple projects: conducting literature reviews, coding data, performing statistical analyses, and running experiments through the Behavioral Research lab. 

In addition, the interns take part in a weekly research seminar series with faculty, allowing the interns to be exposed to the variety of research performed in the business school.  The experience culminates with each intern presenting their work to the CBS research community.  

The internship is a full-time salaried program.  Currently, the program is operating remotely due to the pandemic.  

Successful Applicant Profile

This is a multi-disciplinary program and candidates from all backgrounds, including business, statistics, mathematics, engineering, computer science, the physical sciences, and the social and behavioral sciences are encouraged to apply. We are especially interested in applicants who are underrepresented minorities.

Prospective interns should demonstrate an enthusiasm for research and intellectual curiosity. They are expected to have excellent communication skills, basic knowledge of statistics and/or econometrics, and familiarity with statistical and computational software packages (e.g., Matlab, R, STATA, SPSS) and scripting languages such as Python or R. Candidates interested in working with behavioral researchers should have experience conducting experiments and coding data.

The internship program is designed for undergraduate students in their sophomore or junior year and first year master’s students. Exceptional students from other classes are considered on a case-by-case basis.

For more information

Please email us at [email protected].