Big Data is such a fast-growing field that employers are still figuring out exactly which mix of skills they really need. Even so, they’re hiring like mad.
FORTUNE — Dear Annie: I am expecting to be laid off by a major investment bank (as part of a restructuring the company recently announced) and, instead of trying to find another Wall Street job, I’d like to go into some other business. The conventional wisdom about changing careers is, go where there is lots of growth, and I keep reading about the explosion in companies’ use of Big Data, so I’m wondering: What would it take to get a foot in the door in that field?
I have some on-the-job experience with econometric modeling, and I’ve picked up some basic programming skills along the way, but I’m neither a statistician, a mathematician, nor a software expert. Do I have a shot anyway? What skills are Big Data employers looking for? — No Einstein
Dear N.E.: You’re certainly right that Big Data — also called data analytics or predictive analytics — is growing fast and generating loads of new jobs. Online help-wanted ads for data analysis mavens have shot up 46% since April 2011, and 246% since April 2009, to over 31,000 openings now, according to job-market trackers Wanted Analytics. Salaries mentioned in those job ads range from $73,450 to $89,750. (That’s probably a lot less than you’ve been making on Wall Street — but then, you already know that almost anywhere you go from there is likely to involve a pay cut, right?)
The phenomenal growth in demand for Big Data talent is apparently set to continue. A recent survey of Fortune 500 companies, by consultants New Vantage Partners, found that 85% have either launched Big Data projects or are planning to do so, and that their spending on data analysis will jump by an average of 36% over the next several years. No wonder, then, that Harvard Business Review, in an article last October, called data analytics “the sexiest job of the 21st century.”
“Demand for data scientists is definitely outstripping supply,” notes Andrew Jennings. “It has been for a few years now.” Jennings is chief analytics officer at FICO, one of the giants in the industry. Based in San Jose, FICO tackles Big Data projects for clients in banking, insurance, health care, retail, and government agencies worldwide. The firm now employs about 250 data scientists and, says Jennings, “we’re looking for more all the time.”
So what does it take to get one of those jobs? That’s a more complicated question than it might seem. The field has grown so quickly and seems to call for such unusual combinations of skills, that specific hiring criteria are all over the map. For instance, some employers require you to know a particular set of programming languages, while others couldn’t care less.
FICO FICO is a case in point. On the one hand, if you apply there, your experience with econometric modeling and basic programming could come in handy. “We usually hire people with some quant background, from pure math and engineering to statistics to econometric models,” says Jennings, whose own background is in econometrics. “It also helps to be able to write enough code to link data sets together.”
But on the other hand, how much math and computer expertise you need depends on the role an employer is trying to fill at any given moment. “If you’re not a pure-math person or an expert programmer, that’s all right, because you can be on a team with people who are,” Jennings says. “Apart from the quantitative aspects, there is a tremendous need for people who are inquisitive by nature, who are curious, and who have a talent for figuring out business problems and communicating with clients. If you can help a client understand the crux of a situation and then translate the data scientists’ solution to it into plain English, you’ll be a star.”
Adam Charlson agrees. “The job of product manager is where Big Data begins and ends,” he says. Head of Western U.S. recruiting for executive search firm DHR International, Charlson has helped FICO, Experian, Google goog , HP hpq , PayPal, and many others fill Big Data jobs.
A product manager, he explains, “works with the client to identify a challenge and then takes it to the quant jocks, who build a mathematical model to address it. Then the product manager goes back to the client and explains the findings. It’s about strategy, creativity, and the ability to communicate. If you have all that, math or programming skills aren’t so important.”
These days, Charlson notes, the career path for data scientists and product managers can lead all the way to the C-suite. “There is enormous growth in demand for chief data officers at companies,” he says. “It’s the first time we’ve seen a new C-suite title added in large numbers since the wave of chief information officers back in the ‘90s.”
Note to students who are trying to choose a college or a major: Have you thought about data science? Carnegie Mellon University and M.I.T. have well-established data science degree programs, as does the University of North Carolina, and many other colleges are adding them. There is also a brand new certification program in Big Data, offered by analytics professional association INFORMS, that is designed to provide a standardized credential in the field.
“Predictive analytics is such a new thing that, five or seven years ago, nobody outside of academia was even doing it,” Charlson says. “But now, it’s gone mainstream. If you study data science, and you’re good at it, there will be a job for you after graduation, guaranteed.” That’s something today’s college students, not to mention their tuition-paying parents, rarely hear.