Bridging the Talent Gap: How to Find the Right Data Scientist

  • Renee Boucher Ferguson
  • January 09, 2013

What can companies do to help fill their data scientist gap? That was the topic at a recent conference hosted by the MIT Center for Digital Business.

What can companies do to help bridge their data scientist gap? That was the topic at a recent conference hosted by the MIT Center for Digital Business.

Image courtesy of Flickr user Andrew C Mace.

Claudia Perlich, chief scientist at Media6Degrees, is teaching a graduate MBA course at New York University called “Data Mining and Business Intelligence.”

Google Research senior statistician Rachel Schutt is teaching “Introduction to Data Science” at Columbia University.

It’s this trend in educating a new cadre of data scientists — hiring faculty with both practical and theoretical skills — that will help solve some of the talent shortages organizations are facing in the era of big data. But what should organizations do now, before those newly minted data scientists graduate?

In a recent day-long conference, Big Data: The Management Revolution, hosted by the MIT Center for Digital Business, the practice of finding and hiring data scientists was pondered by three panelists: Perlich, Schutt and Thomas H. Davenport, visiting professor at Harvard Business School and author of the upcoming book Keeping Up With the Quants (Harvard Business Review Press, June 2013). What can companies do in the next thirty days, or the next six months, to help fill their data scientist gap? MIT’s Erik Brynjolfsson, Director at the Center, posed this question to the panel.

Here is their advice:

  • Claudia Perlich: “Take inventory of the people you have already. Make sure they are not marginalized. Make them feel more important. You probably have someone with that skill set. See how you can push them a little bit more into the business side, or someone in business, to the data side.”
  • Rachel Schutt: “Really value data and examine your data strategy. How are you currently using data? Longer term, believe in the notion of teams that can collaborate. Put people with business savvy skills along with those that have data skills. Put data people in executive level positions so they are interacting with decision makers.”
  • Tom Davenport: “What key decisions do you need to make; what product areas do you need to build in? Is it big data or is it small? That will drive the big data and analytics strategy. EMC is creating an internal training program. That’s a smart thing to do.