Rahul Subramanian‘s interest in mathematics began during childhood. He studied computer and information sciences at Rashtreeya Vidyalaya College of Engineering in Bangalore before enrolling in the M.S. in Data Science program at Columbia University.
The 2022 alumnus has sharpened his data science skills through projects with retail and fashion giant Ralph Lauren; Makemytrip, which is considered the Expedia of India; and Orenda, a renewable energy storage company. He will join JPMorgan Chase as a risk data science associate.
Here, Subramanian shares his academic trajectory, his experiences at Columbia during the COVID-19 pandemic, and his future in data science.
What helped to pique your interest in data science?
My interest in data science piqued when I worked as an intern in the e-commerce division of Makemytrip. The project was called the “Travel Inspiration Project,” and my role was to assist my mentor in building a recommendation system model that suggested different travel destinations. I really enjoyed working on the project, and the accolades I received for my work propelled me to pursue more projects in the field of data science.
Why did you choose to come to Columbia for the M.S. in Data Science program?
The curriculum offers a perfect balance with the right amount of computer science-related subjects and statistics-related subjects. Furthermore, you could choose your electives to engineer your profile in the direction of the jobs you want to apply to or research you want to pursue. All of this, coupled with the reputation of Columbia University, made it my number one choice when applying to different universities for my master’s.
How did your undergraduate experience at R.V. College of Engineering prepare you for Columbia?
My college life could be best described as hectic, but fun. I was exposed to a variety of core academic coursework that adhered to my interest, ranging from calculus and algebra to data science and database management. This was accompanied by elective courses, such as natural language processing and big data.
What was your favorite data science course at Columbia?
My favorite course was Applied Machine Learning taught by Vijay Pappu. Everyone is familiar with the conventional techniques and terms in the machine learning space, but knowing which technique to apply in an industrial setting is a skill that the vast majority does not possess. The course taught me several tips and tricks on how to improve the accuracy of machine learning models we build and also gave me an intuition on why the accuracy improved.
Tell us a bit about your capstone project with Ralph Lauren.
I worked on “Market Basket Analysis” with four other members of my data science cohort to help understand factors causing changes in purchase behavior in test and control stores. We presented our findings from the project to the vice president of analytics.
How did your internship with Orenda, Inc. challenge you?
My role in the company was to build a model that would predict prices in the Texas energy markets. Getting to work on such a niche yet challenging problem immensely helped in improving my knowledge in the field of data science. I worked on the problem end-to-end, and, in turn, this helped me to understand the entire workflow of a typical industry-level machine learning problem.
How did the pandemic impact your experience during the M.S. in Data Science program?
A lot of the arrangements were made online and hybrid, and we did miss out on quite a few university life events. Fortunately, Fall 2021 and Spring 2022 were in-person. The increased graduate social events in Spring 2022 made up for the time we lost as a result of the pandemic.
What do you enjoy most about living in New York City?
I can assure you that the hype is totally justified. Despite living in Mumbai, a city that is known to be very cosmopolitan in nature, my exposure levels have risen significantly in New York. The vast variety of cultures you get to see and interact with is just phenomenal. You get to learn about the history and mannerisms of different nations and that has played a pivotal role in making me grow as a person.
What else did you gain through your experiences at Columbia?
[The Data Science Institute] has a great alumni network. The program—and being a part of the DSI Student Council—taught me to leverage this network to help improve my understanding of the industry.
What are you currently working on that you are most passionate about?
I’m currently working on my project titled Certifyde, which is an end-to-end solution that caters to the needs of both candidates and recruiters. For candidates, it offers a way to keep track of their ongoing and completed courses across multiple course platforms (i.e. Coursera, Udemy, Udacity), and it recommends courses based on their interests and previous courses. For recruiters, it offers a way to view and contact prospective candidates based on their area of interest and completed courses.
This interview has been edited and condensed for clarity.