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Just because your competitors are falling over each other in hiring data scientists doesn’t mean you have to grab the next one that walks in off the street.

Stephen Gatchell, head of data governance at Bose Corporation, says that organizations must first figure out why they need a data scientist and how one should be used before they even ask for resumes.

Speaking in a roundtable at the recent Global Artificial Intelligence Conference in Boston, Gatchell also suggested that industry groups could cooperate to lay a firm foundation for data management success.

Here is an excerpt from Gatchell’s interview on SearchCIO.com:

The first challenge stems from hiring data scientists before a company is even ready to hire a data scientist — just because the industry says it should be hiring them. [You need a] concept of the business use cases and what problems you’re trying to solve. It seems like a lot of companies are hiring data scientists but they don’t understand why they’re hiring them. Then, once they do hire them, there isn’t enough data to train those data scientists and for them to have the proper material to get the company’s expected results.

In terms of the [challenge of having] quality of data, I think data quality is overrated. You can never wait until you have enough good quality data if you want to do machine learning and AI because you’re going to wait forever for it.

I also don’t think there are enough industry groups that come together — even though they may be in competition — to consolidate some of their information. I think there’s plenty of data out there, it’s just a matter of collecting the data together and utilizing it effectively.