Can You See The Real Me? Vivienne Ming's Incredible Story of Self-Discovery
The basic premise of Gild is this: Right now, in Bangalore or Berlin or Branson, Missouri, there's a self-taught computer programmer who can code just as well as half the hotshot Stanford and MIT grads currently vying for the world's most coveted software engineering jobs, but no Silicon Valley company has the time or capacity to discover him.
Which is where Gild steps in. Ostensibly, the company is an HR consultancy, doing recruiting legwork for outfits in need of fresh blood. But at its core, Gild is a matchmaker, uniting programmers with the jobs that best fit their skills—and, by extension, that best allow them to fulfill their potential. To find these people, Gild deploys sophisticated software to scour the Internet's open-source Web sites, like GitHub and SourceForge, where software engineers share computer code that's visible to anyone who cares to read it. In seconds Gild's program makes thousands of observations about that code, evaluating its idiosyncrasies to divine insights about its author. It also searches for ancillary information about each programmer—via his LinkedIn page or Twitter account.
These data are plugged into the Gild algorithms; each tidbit, however small, is a valuable clue. If a software engineer tweets "I love celery," it's possible, if unlikely, that he's referring to the vegetable—it's much more probable, Ming says, "that he's talking about Celery, the multiprocessing framework for Python, a popular programming language. And if he uses Celery, he almost certainly uses RabbitMQ or Lettuce, and if he uses those he's probably making Web apps using Flask or Django, and if he uses Django, he knows all about templating languages like Jinja...and that single tweet suddenly paints a rich picture of this person, in a way that listing 'Python' on a résumé would not."
When a company comes to Gild for hiring recommendations, Ming can scour her data and offer concrete, personalized advice tailored to its particular needs. "We'll say, 'Here are ten people,'" she says. "'Three of them are great programmers from big-name schools, and this is the premium you'll pay for them. Now here are five people who are just as good but don't have those credentials; this is how much they'll cost. And here are two people who are also just as good, but who have no credentials. And this is how much you're going to save if you hire them.'"
What's presented as a shrewd cost-cutting measure becomes, in effect, a stealthy upending of the old, outdated rules: A candidate without traditional bona fides gets a chance, and the company giving them that chance gets a great deal. It's a classic win-win.
Next: Evan and Norma's early days