When she was a sophomore at the University of Rochester, Kelly (Ling) He read a book about how big data was destined to transform the way we live, work, and think. The book hooked her on data science, and she went on to graduate Phi Beta Kappa and magna cum laude with both a B.A. in mathematics and B.S. in data science. He, who is originally from Hangzhou, Zhejiang, China, enrolled in the master’s degree program through the Data Science Institute (DSI) at Columbia University after working for EY as a technology consultant. Today, the 2020 alumna is an institutional equity strats associate at Morgan Stanley, an opportunity she secured after a successful summer internship during her graduate studies.

Which book piqued your interest in data science?

I read Big Data: A Revolution That Will Transform How We Live, Work, and Think by Kenneth Cukier and Viktor Mayer-Schönberger during my sophomore year in college. I picked it up in an airport, and finished it during the flight. It was a great introductory book and made me realize that my interests in analytics and computer science at the time perfectly fit into this new field called data science.

Tell us about the internship that led to your current job at Morgan Stanley.

I had a summer internship as a quantitative strategist during my DSI studies. It was a challenging, yet rewarding experience. I was able to explore and learn how data science knowledge can be leveraged and applied in finance. More importantly, I realized that the skill of formulating an unfamiliar business problem, and matching it with the most suitable data science solution, is essential in our field. And it will take time to master.

What were your favorite courses at DSI?

I enjoyed Eleni Drinea’s algorithm class, which is fundamental to understanding and solving many data science problems. I also liked John Paisley’s machine learning class because he is great at dissecting complex concepts into small pieces and explaining them in a simple way that everyone can easily understand. In addition, Andreas Mueller’s applied machine learning is extremely useful for quick prototyping in practice.

What did you enjoy most about studying in New York City?

I worked for a year in NYC before attending Columbia. I’ve always dreamed of living here while being an independent adult for the first time. It didn’t let me down. I love that I can easily keep in touch with my friends; I love that I can take a stroll in Central Park anytime; and I love all the exciting learning and networking opportunities the city presents.

What were three things you gained from the DSI experience?

Met incredible faculty members and peers; worked on a variety of projects that focus on different aspects of data science; further nurtured my passion for data science even after realizing the potential obstacles that I need to overcome along the way.

— Sharnice Ottley