Wanted: Job candidates with diverse backgrounds to fill severe big-data jobs shortage

Companies urgently seek people with IT, math and business backgrounds

By , IDG News Service |  IT Management

DataXu, a Boston company that offers a product for managing online advertising campaigns, also takes a team approach to filling data science jobs, says CTO Bill Simmons. Big data workers there have strong math and coding skills and some business savvy, he says.

People who excel in one area, are strong at a second and have a grasp of the third allow the company to form teams based on different strengths.

Possessing "two out of the three is what you need to get the job done," he says, adding that finding people who have a strong background in one of those areas is fairly easy. Standouts in all three skills are harder to come by. "I would be delighted finding someone who is a star in all three areas."

Employers also seek workers whose software skills and data backgrounds match their work environments.

Companies select database software that can handle their data sets, which can be complex, says Rob Byron, a principal consultant in the information technology division of staffing firm Winter, Wyman. Employees, for their part, prefer to stick with the software they know.

"The general outlook is if we have a SQL server data warehouse I'm looking for Microsoft [skills]. Oracle people need not apply. And vice versa. And quite frankly a lot of candidates don't want to learn new skills," he says.

Given the amount of data companies are dealing with, they only want candidates who have handled that volume, says Modis' Kelley. A person's data experience, not the industry they're in, is what matters to employers, she notes.

"Data is data," she says. "Industry vertical really isn't going to be the key driver. Its going to be what did you do with the data, how large of an environment was it."

Firms will avoid candidates who have only worked in smaller environments because at "very large enterprise big data programs ... you're talking about huge amounts of data and that could be very overwhelming to someone."

While IT professionals have a grasp of what traits work for data science's technical positions, defining what backgrounds make for a good analyst proves difficult.

These positions go beyond possessing strong technology skills so being a solid developer does not necessarily translate to an analyst job. Companies need employees who can make the data work for the business.

"Companies are really looking for higher level quantitative skill sets for these roles," says Kelley. "It's not every developer you come across. It's someone with that business acumen who can parlay those skills into strategic decision making."

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