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May 6, 2013

Raising a Pack of Data Scientists

Ian Armas Foster

According to the McKinsey Global Institute, by the year 2018 there will exist 190,000 unfilled data scientist positions. North Carolina State University is one of the educational institutions looking to assemble a curriculum and a program that helps fill those jobs.

That looming gap of nearly 200,000 in five years exists mainly because institutions are largely unsure as to what makes a decent data scientist. “Big data is like a kids’ soccer game,” said Greg Meyers, CIO of Biogen Idec. “Everyone is running to the ball, but no one knows exactly what to do with it. It has created a huge competition for people.”

Things like Kaggle, which use competitions to sift through thousands of prospects and determine the best writers of big data analysis algorithms, help to a certain extent. But still, it’s difficult to understand which sort of backgrounds generate a higher level of data expertise, especially when considering that different organizations want their big data to do drastically different things.

Of course, some sort of computer science background is required. Additional computational physics training can be of assistance as it usually demonstrates an aptitude for complex problem solving.

“It’s a very fluid area,” said Michael Rappa, executive director of the Institute for Advanced Analytics at NC State. “Depending on what industry you’re in or what company you talk to, it’s a different reality when you talk about big data.”

Rappa hopes to be instrumental in creating and identifying the next generation of data scientists through the aforementioned Institute for Advanced Analytics at NC State. “Big data is about taking all of that data together and using it to optimize business or inventory levels or to better target customers,” Rappa noted on one of the commonalities among organizations looking to leverage big data. “That’s the trick of the whole thing. You need people who are good at handling large volumes of data and have knowledge of math and statistics to analyze the data.”

Further, according to Rappa, employers also look to those who work well in a collaborative setting, similar to that of IBM’s analytics setup. As such, the NC State program reportedly pulls people together from various disciplines, including math, business, and computer science.

The program lasts five days a week for ten months and awards graduates a master of science degree upon its completion. Those ten months are reportedly spent practicing with real datasets from companies like GE and GlaxoSmithKline, an important consideration when taking into account last week’s article on how large datasets are largely unavailable for big data educators.

The Institute at NC State has been around since 2005. In that time, seventy percent of its candidates have come from companies looking to elevate talented IT individuals to big data analysts and scientists. A program like this, if successful, won’t fill the demand by itself. But it could set the template for other research universities to implement similar institutions.

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