Want to extract real value from your data? Better hire a data scientist or two.
In the past several months, large enterprises, staffing firms and universities have observed increasing interest in a new class of data professional -- the data scientist. A curious blend of business, analytics, and computer skills, this hot new title is on the march in diverse verticals such as energy, e-commerce, healthcare, and financial services. And if experts are correct, this is just the beginning. (See also: Who's hiring data scientists? Facebook, Google, StumbleUpon and more.)
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"Companies are becoming so data- and application-centric. They need individuals who can come to the table to model and mine in big data environments," says Laura Kelley, Houston vice president at IT consulting and staffing firm Modis.
What sets data scientists apart from other data workers, including data analysts, is their ability to create logic behind the data that leads to business decisions. "Data scientists extract data, formulate models and apply quantitative analysis in a proactive manner," Kelley says.
These hefty responsibilities lead to a commanding salary -- $110,000 to $140,000 across the country, Kelley has found. "There are data scientist jobs available today - you just have to have the right combination of skills," she says.
Enter Michael Rappa, director of the Institute for Advanced Analytics at North Carolina State University in Raleigh. For the past six years, Rappa and his fellow professors have been refining their graduate program to develop ready-made data scientists.
"Data scientists have to draw structured and unstructured data from different sources, including real-time streams, and try to understand it to add value to the business," Rappa says. "It's not just about the volume of the data, but the variety and velocity of it."
Companies that attempt to handle big data with siloed statisticians, computer scientists or MBAs will fail, Rappa believes. Instead, they need professionals with a convergence of these skills to fully grasp the business and technological challenges.
MBAs understand business concepts such as product development and management, but aren't able to analyze and interpret data. Mathematicians and statisticians lack intimate knowledge of the business. "Data scientists must have an openness to solving business problems, not just be able to perform some nifty modeling. We educate students in a way that cuts across disciplines," Rappa says.
The approach has been proven out as 100 percent of the program's participants are placed before graduation. "They are highly sought after and highly paid," he says. In fact, the program recently expanded its annual enrollment from 40 to 80. "We doubled the size to meet the demand coming from the private and public sectors."