If you're thinking, "Well, I'll just send my recruiters to LinkedIn to scour for talent," I have news for you: It's not going to work. Running the numbers, Vicki Boykis has persuasively argued that there simply aren't enough people to fill all the data science jobs on the market. And if you're hoping for a qualified person (rather than digging into the "oversupply of junior data scientists hoping to enter the industry [with] mismatched expectations on what they can hope to find once they do get that coveted title of 'data scientist'"), well, good luck with that.
For years we've been told that data science is the future; that artificial intelligence (AI) and machine learning (ML) will enable us to automate everything. And yet most (85%) data science projects fail, according to a 2019 report, though such scare statistics might not reflect reality. Still, there are plenty of reasons why a data science project might not work as advertised, but one reason stands out: Talent. Or, rather, the lack thereof, as Gartner has highlighted.