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."
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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2. Look Internally
Soderstrom is undertaking a thorough search for external candidates, but he's also aware of the possibility of grooming internal candidates -- an option that is usually cheaper and has the added benefit that the person would be familiar with the JPL's environment and customers.
Looking at mid-level engineers and programmers, Soderstrom says he is "shaking the trees to see what comes out." He plans to hire a data scientist this month and surround that person with interns to help with some of the legwork. He also wants to carve out a career track for interns to become data scientists.
Reed recommends investigating whether there are employees who have the raw analytics skills and would benefit from an investment in training. He says the only downside is that internal candidates still have to learn as they go and may not be as proficient at certain tasks.
3. Sell Them on Your Company
If your company decides to fish in the pool of external candidates, Reed says it's important to have a strong and compelling story to tell because the up-and-coming tech firms and hot startups will be tough competitors for talent.
"You have a cool story to tell if you work for Google or Facebook, but what if you don't?" he says. "You have to get them excited about working [for your company]. You are selling them on joining your organization. Unless you offer compensation and benefits and have a great story to tell, these people will [only] want to work on the coolest projects out there."
4. Look for Consulting Skills
JPL's Soderstrom says that one of the qualities he looks for in candidates is a consultant mindset. "A good consultant goes in and talks to a customer with a problem," he says. "He understands the problem and comes up with a creative solution with the customer."
If you're unable to find a person with that mindset, using an external consultant may be your next best bet. Reed suggests enlisting one if the idea of growing your own data scientists isn't appealing or won't work for your company. But he warns against hiring someone who "may have the academic side of it, but not the practical work experience."
5. Join Networking and Technical User Groups
To find candidates for a data scientist job, you need to find out where the candidates spend time. Reed recommends making yourself and your company visible. "You have to make sure these people can find you where they go to network." Reed suggests joining LinkedIn groups, social media groups and technical user groups. "Go on an awareness campaign," he says.
Until universities produce more graduates with big data skills to address the shortage, CIOs will need to be creative to find people with the right skills and the right fit for their big data aspirations.