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  • Thomas Thurston

Could data science someday disrupt HR recruiting?

Updated: Apr 3

Got a nice email from Simone a while ago and now finally getting my act together to share it with everyone (thanks for your patience Simone!). She passed along a very cool article in the NY Times about how data scientist Luca Bonmassar (co-founder and CTO of startup Gild) is using algorithms to evaluate software developer job candidates.


hiring

It can be really, really hard to find awesome developers. This is especially the case with “big data” experts who truly understand data science. Sometimes these people are well known, but a lot of times they’re quietly doing magic in a cave somewhere relatively unnoticed by the rest of the world. That’s why Bonmassar is using data science to find talent and evaluate job applicants.


Bonmassar and his colleagues do this by scraping info. from the Internet and using algorithms to crunch thousands of variables about people such as the sites they hang out in, the words they use, how others describe them, projects they’ve worked on, and so forth. It uses this data to get a better sense of job applicants and for spotting diamonds in the rough. Gild isn’t alone; other firms like TalentBinRemarkableHire and Entelo are in the race too, albeit through slightly different approaches.


Could HR recruiters someday be disrupted by data science?  If so, would that be a good thing or bad?


Imagine a world where job applicants are found and evaluated by their merits and contributions, rather than by how well they sell themselves in an interview or who they buy enough beers for. Sometimes it seems like getting a developer job can be more about hanging with the “cool kids” as opposed to raw results and talent. In that sense, a more merit-centric world governed by algorithms can seem more productive and fair. On the other hand, could an algorithm detect if someone’s a jerk? Are they a good fit for a firm’s culture? Are they a meth-head? Are there things only a human HR recruiter can do?


I think there are pros and cons for using algorithms like these, but I must confess I’m optimistic. There are some things human brains are good at, but other things algorithms excel at. Ultimately the best hires will go to those with the right combination of human-mechanical processes in their search for top talent.  You can’t ignore the “human” element, but you’d also be remiss to ignore the science.

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