CIO — Load the term "data scientist" into Dice.com's and Monster.com's search engines, and you'll get eight and seven responses respectively. Clearly, data scientists—the brainy, analytical folks who are charged with using statistical modeling tools to draw insights from huge quantities of data—laren't in demand today the way software engineers are, but experts in the field of data mining and data science believe that's going to change.

Brian Hopkins, a principal analyst with Forrester Research (FORR) who specializes in enterprise architecture with a focus on emerging information management technologies, anticipates demand for data scientists to grow as companies increasingly seek a competitive advantage from the massive amounts of data they collect and as they realize they're not getting the wisdom they need from existing data mining and business intelligence tools alone.

"Companies are always looking for ways to know more than their competitors," says Hopkins. "There's this notion that if they buy some predictive analytics tools, the tools will give them insight. [In fact,] You need this specialized class of data scientist to create and run [statistical] models against data and present the results in ways people can act on."

The limitations of existing business intelligence software combined with the maturation of parallel computing and sophisticated data modeling tools have paved the way for the data scientist's emergence, according to Steve Hillion, vice president of analytics with data storage company EMC (EMC). Like Hopkins, Hillion agrees that companies are beginning to realize they can't rely on software alone to make sense of their terabytes of data. They need individuals with highly specialized skills, and those individuals require special technology. Hillion says the hardware and software data scientists use to perform their analysis is now robust, scalable and cheap enough that a variety of companies in different industries can use it.

Hillion spoke to CIO.com about the burgeoning data scientist role, the industries where they're most in demand, the skills they need, where they sit in organizations, and what the role means for business intelligence software.

CIO: What is a data scientist?

Steve Hillion, Vice President of Analytics, EMC: Somebody who is charged with creating insights from large quantities of data using computer-based analytical and modeling techniques. The job is about applying the methods of data mining, statistics and modeling to large quantities of data, typically to generate business insights or identify underlying trends or patterns.

What kinds of businesses need data scientists?

You'll typically find a data scientist or data analyst in large organizations that gather a great deal of consumer data, whether that's a Web company, an advertising network, a cell phone company or a retail company that tracks sales or marketing data.

Is this a new role? Haven't companies had people in charge of analyzing data before?

If you look at retail companies, consumer goods companies like Coca-Cola (KO) or Procter & Gamble (PG), they've long had researchers, statisticians who have [for example] applied econometrics techniques to understand pricing and customer data.

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