More than 1,700 students applied to the master’s in data science program, making it the most competitive year yet for acceptance into the program.
The academic profile of the class is exceptional. The 172 students have an undergraduate average GPA of 3.76, and they also excelled on the GRE; their average quantitative score is 168 and verbal is 158. Though the majority (65 percent) have engineering or technical degrees, and 23 percent studied math or statistics, about 10 percent of them studied subjects such as actuarial science, cognitive psychology, finance, physics, international studies and sociology.
About 80 percent are from abroad, coming from 13 countries such as China, India, Korea, France and Mexico. The majority of them are recent graduates, having finished undergraduate school within six months of starting the master’s program. Their average age is 24, and 42 percent are women, an increased representation of 5 percent from last year.
During the recent orientation for the incoming class, Jeannette M. Wing, the Avanessians Director of the Data Science Institute, welcomed the students and gave them an overview of her three-pronged mission for the institute, which she said could be summed with three little words: “Data for good.”
“Data science is a new and emerging field, so you are all trailblazers,” said Wing, “and this is the most rigorous data science training program on the planet. But all of you are super qualified and after you graduate you can work in any profession you like. You’ll be sought after and be able to choose your future path. We just hope you’ll use data to do good and to help society.”
Overall, students in the class said they were drawn to the Master of Science in Data Science and the Certification of Professional Achievement in Data Science programs because of the varied course offerings, Columbia’s well-known professors and its location in New York City, which offers unparalleled cultural and career opportunities.
Discovering Data Science:
Consider, for example, incoming master’s student Romane Goldmuntz. She grew up in Belgium, where as an undergraduate she studied business engineering at the Université Libre de Bruxelles; she also later earned a master’s in business economics from the university. Afterward, she worked as a software engineer in Belgium for Accenture. She was passionate about data science, which she had discovered as an undergraduate when she heard a lecture by Sebastien Deletaille, co-founder of Real Impact Analytics. After working for Accenture for two years, however, she realized that data science had not taken hold in Belgium and that none of her clients were using it.
“I realized that if I wanted to become a data scientist and learn how to create models and apply machine learning techniques,” said Goldmuntz, “Belgium was not the place to be.”
She researched data science programs and learned that the U.S. was advanced in data science and that Columbia in particular had a prominent master’s program. Healthcare is the field she eventually wants to work in and she saw that the master’s program offers several electives in various aspects of healthcare. Now, as a master’s student, her goal is to learn the most advanced data science techniques and to later find a job where she can apply those techniques to the fields of genomics and bioinformatics.
“I’ve been passionate about data science since I first discovered it when I was 19,” said Goldmuntz. “I took courses in computer science and statistics so I’d be better prepared for data science and I’m really excited to begin studying the field I love.”
Moneyball and Data:
When he was in high school, incoming student Shreyas Saipras Jadhav saw the movie “Moneyball,” which dramatizes the story of a pro baseball manager who builds a champion team with a low budget due to his deft use of data science.
“That film sparked my interest in data science,” said Jadhav, who grew up in India and studied computer engineering at the University of Mumbai’s D.J Sanghvi College of Engineering. He took a lot of technical courses at the university, but of all of them he liked data science classes the most. That’s why he applied to the master’s program, where he wants to “strengthen my fundamental understanding of data science and apply that knowledge to improve something that exists or perhaps solve a problem that hasn’t been addressed.” His goal after he graduates is to work for a prominent tech company like Google or Amazon. He loves sports, too, and hopes to found a startup company focused on sports analytics. He’s also thrilled to be living in New York City, which he describes as a friendly and diverse place that reminds him of Mumbai, his home town.
“NYC is amazing,” he said. “The people here are so nice and helpful and they come from all over the world! It’s really mesmerizing to see such diversity. You can visit a museum one day, chill at Central Park the next, or wander around Times Square – there’s nothing you can’t do here.”
And come September, he’s eager to begin studying the field he loves: data science.
“The sheer omnipresence of data in all fields will really allow me to explore and any field I like and to explore the applications of data in those fields,” he said. “Finally, I just feel it’s quite cool when you can predict the future using the past data with a certain amount of accuracy.”
— Robert Florida