Data scientist jobs are hot in the era of big data. These professionals are responsible for manipulating petabytes of data into better decision-making, new streams of revenue and ultimately more business. A study by McKinsey Global Institute shows that a company using big data to its full potential could increase its operating margin by more than 60 percent, but there's a big shortage of talent.
CIOs are struggling to find and hire people with that perfect balance of business acumen, database expertise and effective communication skills. "Everybody wants these people and it's harder to find them," says John Reed, senior executive director at Robert Half Technology, an IT staffing firm. "Because the demand far outweighs the supply, you will have to go to more sources for the right candidates."
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You won't likely find many candidates the phrase "data scientist" on their resume. Some candidates may not even know they are a fit for the data scientist job. Here are five tips for finding and hiring a data scientist.
1. Look for a team instead of one person
You may find candidates with some skills and not others. So you'll have to warm up to the idea that you may not find everything in one person, which means hiring two or more people to fulfill your needs.
According to an EMC survey of 497 data scientists and business intelligence workers, half of big data scientists partner frequently with other data scientists, statisticians or programmers.
Tom Soderstrom, CTO of NASA's Jet Propulsion Laboratory (JPL), says that although he can clearly define the data scientist role at his company, he knows it may be impossible to find. "It's a special type of person and I've discovered that I don't think they exist." Instead, he says, "It could be a team of people. A data scientist could work with several interns and a community around them."
At NASA JPL, Soderstrom sees the potential for data scientists to manipulate satellite data about oceans or weather to develop new types of science experiments. He says he's looking for someone who can both speak the language of business and work with big data technologies, such as Hadoop. "It's someone who can teach data to tell an interesting story that we didn't already know."
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