How To Build A Successful Data Science Team

Published December 31, 2013   |   
Jeff Bertolucci

Is there really a data scientist shortage, or are organizations simply trying too hard to recruit a unicorn, a jack-of-all-trades who possesses both advanced technical and business acumen?

If the unicorn hypothesis is true, it would explain why the scarcity of data scientists is expected to worsen in the coming years.

The solution isn’t difficult, some industry insiders believe, but rather one that might prove unpopular with cost-conscious organizations unable or unwilling to hire a data science team rather than a single data scientist.

Dr. Michael Wu is chief scientist of Lithium Technologies, a San Francisco-based company that sells social customer experience management software to businesses. Not surprisingly, Lithium captures a lot of data on consumer behavior, and part of Wu’s job is to analyze that information and predict customer actions on an aggregate level.

Wu believes term data scientist is tossed around loosely these days, so much so that it’s creating a bit of confusion in the tech industry.

“What the industry calls a ‘data scientist’ now is really several different roles,” said Wu in a phone interview with InformationWeek. “When people say there’s a shortage of data scientists, (they mean) there is a shortage of people with all of these different skills.”

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