With all the talk of big data these days, many businesses are still looking for talent to turn massive amounts of information into something they can use. New York University announced Tuesday it is creating a Center for Data Science, along with a master’s-level degree program to train big-data professionals for commercial and public sectors.
“There’s a continuous flow of data coming from customers and sensors,” says Yann LeCun, director of the new center. “Companies have to make sense out of it.”
Making more efficient use of big data is growing more critical to business, research, and government entities. NYU sees increasing demand for experts to better harness big data to work in industries that include sensors, e-commerce, and media. “It is very difficult to find data scientists right now on the job market,” LeCun says. “It’s because there is no place to learn data science.”
The theme for the new center, he says, is to bring together people from different academic disciplines such as mathematics, computer science, and statistics. He explains that computer scientists might not know enough math to fill data science jobs, while mathematicians might not know enough computer science. Statisticians also might not be fluent with the computational tools of computer science.
“We’re also bringing together people who have data problems—data they want to extract knowledge from,” LeCun says. The center will be housed at the university’s Courant Institute of Mathematical Sciences and will strive to collaborate with companies such as Google and Facebook that want to leverage information from big data as part of their businesses.
Smaller companies with access to large amounts of data may also want to collaborate with the center, according to LeCun. “Sometimes they have data that can be pooled with other people in their industries,” he says.
Why the business interest? Data scientists can help e-commerce companies better understand and target their customers. “If people are buying stuff from your website, you want to propose things they are likely to buy,” LeCun says. “There are tools to do this at a simple level, [but] to do this to scale is kind of difficult.”
For example, pharmaceutical companies, he says, with vast amounts of data on clinical trials and health insurance companies with information on patients could use data science to help develop suggestions on treatment or courses of action. Utility companies might use big data to better predict system failures or increases in power consumption.
NYU wants to establish partnerships with companies to serve as mentors for students in the program, who must complete capstone projects at the end of their studies. Each project would typically be proposed by a partner company and partially advised by someone from that company. “Students will be confronted with the real world, and the company gets a preview of the students’ skills—and perhaps some useful developments on their problem,” LeCun says.
Companies might send scientists in residence to work with researchers and faculty at the center to gain new expertise. The companies would also be able take on students as summer interns. And there may be opportunities for companies to fund research projects they are interested in.
The data science center will start taking applications this month, with the master’s program expected to launch in the fall with about 25 students. LeCun says 50 to 60 students will annually be accepted going forward into the two-year master’s program. Plans for a doctoral program are also in the works.
