Data science education has to go broader to serve the next generation of tech talent

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The global talent shortage for next generation technology has been well documented. McKinsey predicts that while the number of data scientist job openings in the U.S. will hit 490,000 by 2018, fewer than 200,000 data scientists will be available to fill those spots. And as more advanced technologies like artificial intelligence and cognitive computing start to take hold, it’s likely the shortage will get worse — tech companies are already in a scramble to hire talent in artificial intelligence, poaching researchers and Ph.D. candidates from universities. So will we have enough skilled workers with the particular training needed to sustain the growth of these promising technologies? Some experts argue this is the wrong question to ask.

“What’s most important is to educate students who can think, solve problems, and retrain themselves as technology changes in the future, ” says Hank Levy, head of the University of Washington’s computer-science program. “These skills are more important than specific technologies and most top companies interview for these skills.”

Rather than focusing only on building up expertise in computer science knowledge, Levy argues the education system also needs to teach students a broader set of skills, including business and communication expertise and — most critically — adaptability and continuous learning.

“It’s impossible for us to educate students in every part of computing and in every technology, which is why we want students to be able to continually learn in the future, ” says Levy.

Michael Rappa, founding director of North Carolina State University’s Institute for Advanced Analytics, argues that companies can usually find people with technical skills in programming and data analytics. What’s harder, he says, is finding people who know how to work the process from end-to-end.

“The discussion of the analytics skills gap is missing the target,” says Rappa. “The skills gap is not so much about people not having the requisite technical skill as it is about having a balanced skill set.”

Employees who can do everything from recognizing and framing business problems, modeled with data, to communicating those insights in a way that decision makers can understand and take action seem to be the ideal employees of the future and present in tech.

The education system is responding quickly to address the need for more data science expertise. There are now more than 100 graduate programs in analytics and data science teaching the technical skills. “However, only a small subset of these programs are designed in a manner that will give students an opportunity to learn and master the full spectrum of the analytics process,” says Rappa.

“Data science is fundamentally a discipline that’s blended from a number of fields—it’s part data science, part statistics, part business thinking,” says Amy Gershkoff, chief data officer at Zynga and an adjunct professor at the University of California, Berkeley. The U.S. education system is designed for an individual disciple rather than multi-discipline kinds of study, she explains. Given the application of computer science across the economy and society now, the education system needs to adopt a multidisciplinary approach to preparing people for a career.

Award-winning writer and author of To Catch a Cat

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