How to overcome the data scientist shortage

Implementing successful AI applications has to be supported by a team of data scientists, but the industry is facing a data scientist shortage and skyrocketing salary requirements for these professionals. How can companies tackle the issue?

Amy deCastro, vice president of human resources for the secure power business at Schneider Electric, a multinational energy management and automation company, offers a new perspective to the search for data scientists. She recommends starting by talking to your existing employees, spotting the ones with a passion for data and a semi-technical background, and investing in data science training for them.

Editor's note: The following has been edited for clarity and length.

How can you look internally to overcome the data scientist shortage?

Amy deCastro: There is such a competitive market that we're starting to build from within. Right now we can't necessarily get the formally trained data scientists, because everyone looks at that on a resumé and scoops them up. So instead we've changed our approach and we're just looking for those really strong hires with passion, but because they didn't major in a certain area within a university they're not necessarily getting the same attention as data scientists.

Amy deCastro

We actually have an entry-level data scientist's organization within our facility in Bangalore, India. We have a senior leader -- Dr. Supriya Mitra -- who is actually onboarding a junior workforce and developing that skill set from within, because it is such a challenging market right now.

We're finding people that are open and willing to go down the data science route -- even though they didn't necessarily go to school for it, but [they] have a technical background and we're investing in their education because we know it's so hard to find that skill set. With training, they actually are brought into a more technically challenging role where they can learn quicker, and can apply that more technical skill set sooner.

We're more interested in technical ability and aptitude, but then passion for what we're trying to do. [We look for] interesting people that have the ability to deep dive. So for us, it's a relationship with energy as well. I've talked to people where you ask a question about AI and data and they say, 'I can do pivot tables.' Move on. Then you get people [who say], 'Well, in my freshman year of college we created this and we were able to tie in this,' where you start hearing them be really passionate about what they're doing. That's what we're looking for.