Hiring in Biotech is Tricky. But Algorithms Won’t Save the Day
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landing what sounds like a good gig as an associate scientist with Emergent Biosolutions in Seattle.
Beltran says she didn’t encounter the spelling quizzes or video games described in The New York Times article, but she did find a way around the online filters that probably would have immediately disqualified her from getting the job she got. She used an outplacement firm, got more serious about keeping her network fresh, and added some clever social media skills. (One of her tricks was to use LinkedIn regularly, and occasionally ‘like’ some of my Xconomy articles to stay in touch with me.)
“I had to get re-educated on how to approach the job hunt process. Job hunting, networking, and social media took on a new life, versus what I knew back in 2006,” Beltran said. “I did experience firsthand how important it is to know yourself and your skills set. One has to be succinct and sharp about marketing oneself, especially with recruiters. And yes, it takes a lot of patience with biotech firms. Either it goes into the abyss, processed into the ‘system’ or flat out rejection.”
I’m glad to hear that Beltran found gainful and challenging employment. It took a lot of patience and adaptability. She may not have checked every single box you could imagine for such a position, and I doubt that an algorithm would have pushed her application to the top of the stack.
But if you believe that people are more than a collection of data points, and that attitude is a crucial intangible—like with Jonny Gomes—then I suspect Beltran will be just fine. Someone had to make a subjective, human decision about her. That’s how it’s always been in the hiring game, and how it ought to be. At least, I suppose, until the machines can prove they are better at selecting people than actual people.