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Finding internal data science talent: The right stuff Posted on : Oct 04 - 2018

As companies use big data to better inform decisions, they create more demand for professionals able to grapple with those databases and turn them into assets.

Indeed the competition for recruiting big data science talent is brutal and likely to stay that way for a while. But opportunities exist for CIOs to tap the skills of people in their enterprises.

"This is a massively expanding field and it's going to be that way I think for the next decade," said Fritz Schlereth on a panel at the Global Artificial Intelligence Conference in Boston last week.

Schlereth is head of product at Descartes Labs, a geospatial analytics startup spun out of Los Alamos National Laboratory. He was among a panel of AI experts at the conference who offered advice on how to identify data science talent and how to manage data science teams to yield business results. 

Internal data science talent

One way to acquire data science talent: Look homeward. Solution architect Craig Rowley joined the Columbia Sportswear Company in 2017 with the purpose of building a data science team for the $6 billion retailer.

"This is the first enterprise company I worked at where I actually get to see that phase where we're discovering who those people are that are multidisciplinary," Rowley said.

The people at Columbia who have demonstrated the ability to solve big data questions share certain attributes, Rowley told the conference audience. They typically possess a deep domain expertise. That expertise allows them to define a problem worth pursuing, he said, and to understand the kind of data they will need to solve it.

The case for emotional intelligence

When recruiting big data science talent, John Mercer, the head of data science for the video advertising company Pixability, looks for emotional intelligence first -- and for people who would work well in a team environment. View More