Rappa admits that the term "data scientist" is far more appealing than its piece parts such as statistician and computer scientist. "Data science captures the imagination," he says.
Eric Horn, education director at the Data Sciences Summer Institute at the University of Illinois at Urbana-Champaign, agrees that there is a certain mystique to data science, even though it has a heavy computer science influence.
For instance, his students as well as those at the university's Illinois Informatics Institute are trained in various machine learning algorithms, natural language processing and intelligent search algorithms. They also learn how to apply those algorithms in myriad domains such as healthcare.
Like Rappa, Horn has witnessed heightened interest in his program, but can't expand enrollment at this time due to funding.
Modis' Kelley feels educational opportunities will open up as more companies focus in on data scientist skill sets. She encourages candidates with partial talents - such as an MBA, analytics or computer science - to fill out their resume with degrees or certificates from tailored programs like Rappa's and Horn's. (See also: 10 tech-centric MBA programs.)
The data scientist draft
At eBay's transaction arm PayPal, Chief Scientist Mok Oh is creating a fantasy data scientist team and he's hoping to unearth candidates like those being churned out by the programs at Horn's and Rappa's institutions.
PayPal plans to study the tens of petabytes of data its customers and partners generate to predict buying patterns. Oh wants to carefully blend spending and behavioral data to develop profiles and uncover trends that will help attract new customers to PayPal and its partner ecosystem.
Though Oh's ideal candidate would have all three skill sets -- business, analytics and computer science -- he has not found enough of them. "It's almost impossible to find those three heads in one body," he says. So instead, he's developing a data science team comprising all three disciplines:
*A majority -- 80 percent -- will be PhDs focused on machine learning, natural language processing and data mining.
*10 percent will be statisticians highly skilled in data modeling and analytics to develop key performance metrics.
*Another 10 percent will be MBAs who know the right questions to ask such as "Why do people stop using PayPal?"
Oh is convinced this concentrated team -- vs. dispersed silos of data analysts -- will propel PayPal into the next generation and better serve its customers.
Donald Farmer, vice president of product management at business intelligence software maker QlikView, says most enterprises can make use of data scientists to improve processes and identify new business opportunities. For instance, in financial services, data scientists can develop algorithms for trading and risk management, and in pharmaceuticals they can study drug test results.
Farmer warns, though, that companies who bring on data scientists have to be able to tolerate failure. "Data science is all about experiments. Companies have to create structures at the edge of their organization that are not only entitled but are expected to fail. Otherwise, the data scientists aren't trying hard enough," he says.
It's a tough pill to swallow for cash-strapped organizations. "Sometimes you have to fail at a model to be able to rethink it properly -- but that can be risky and expensive," says Ryan Swanstrom, author of the "Data Science 101", a blog about his journey to become a data scientist.
Given the right environment, data scientists have the potential to strike gold for companies -- especially those focused, like at PayPal, on how to find new customers and improve service to existing customers. Interestingly, Swanstrom feels that shaking up the trifecta of computer science, business and analytics with peripheral fields such as physics and psychology would improve results.
Modis' Kelley labels the data scientist role "a work in progress." "What companies called a data scientist a year ago is different than their requirements today," she says.
The only sure thing, according to Horn, is demand: "With the availability of data, there is certainly going to be opportunity for as many people as want to pursue data scientist training."
Gittlen is a freelance business and technology journalist in the greater Boston area. Email her at email@example.com.
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