Can’t Land That Elusive Data Scientist? That’s Because You’re Going About It All Wrong

If you read the industry rags, you’ll start to believe that data scientists are rarer than diamonds, and more expensive, too. While they certainly aren’t in abundance, you can get a good data scientist if you’re willing to look, willing to pay for one, and a data scientist is actually what you need. Here’s everything you need to know before launching your next head-hunting campaign.

Be Sure Your Organization is Ready for a Data Scientist

Data scientist is actually a broader term than you might think. Within that title exist a wide range of skills sets, some focusing on gaining insight from data on people, while others have experience working with machine data.

Data scientists are not database architects, nor are they data managers or data engineers. Data scientists are trained to walk into a finely structured data warehouse and turn all of that data into meaningful insight. They aren’t the ones to call when you have a mess of a database and need it cleaned up, hung into a framework, and governed.

Be Sure What You Need is a Data Scientist

Similarly, data scientists aren’t data babysitters. They can help you determine where to draw in new data streams and help you maximize the use and value you get from your data. But they aren’t the ones you need if your data isn’t centralized (in other words, if you are still dealing with data silos) and isn’t organized. Data scientists also aren’t the right folks to call if you just want to ask a bunch of questions and get them to find the answers for you. Data scientists are more creative folks — the kind who determine what questions to ask this specific collection of data, and then deriving fabulous ways to glean the answers.

Be Sure You’re Asking for the Right Kind of Data Scientist

You may not find your ideal candidate down the street. Be willing to take your search nationwide, or even worldwide to land the data scientist you need.

While there are data scientists who specialize in specific industries and environments, you can loosely categorize all data scientists into one of two groups: data science for machine data and data science for human data. These two groups, obviously, are trained and experienced in either deriving meaningful insight from machine data for things like operational intelligence, or deriving insight from people data for deriving consumer or business intelligence. There can be some overlap here, but as a general rule, you’ll be looking for one or the other (or perhaps both).

Be Sure You Hire the Right Data Scientist

Finally, you need to make sure you go about your search for a data scientist the right way. Here are a few tips for landing that great white whale:

• Don’t limit yourself to a local search. If you have an intriguing job to offer and the pay is right, your ideal candidate will probably be willing to relocate.
• Don’t be afraid to compete for candidates in the hot markets, like Silicone Valley and NYC. You never know when a perfect candidate might be tired of the bright lights and big city and ready to relocate to your facilities in the farmlands of the Midwest.
• Find out what their previous experience is. While it isn’t impossible to apply skills learned in one sector to another industry, you do want to get experience as close as possible to your types of data and the kinds of analysis you need to do.
• Don’t overlook the importance of corporate culture. Data scientists need to be able to work closely with all other departments and with all other job titles. They won’t just be working with the CIO and IT managers, they’ll also need to be able to communicate well with finance, operations/production, human resources, sales and marketing, R&D, and any other department that needs to deal with data (which today is all of them).

Is your organization looking to make the most out of your big data, but you still have questions and no one to ask? Get more information on hosting your own Big Data Week event by contacting us today.