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.
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