I was discovered by an algorithm
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When the email came out of the blue last summer, offering a shot as a programmer at a San Francisco startup, Jade Dominguez, 26, was living off credit card debt in a rental in South Pasadena, California, while he taught himself programming. He had been an average student in high school and hadn't bothered with college, but someone, somewhere out there in the cloud, thought that he might be brilliant, or at least a diamond in the rough.
That someone was Luca Bonmassar. He had discovered Dominguez using a technology that raises important questions about how people are recruited and hired, and whether great talent is being overlooked along the way. The concept is to focus less than recruiters might on traditional talent markers—a degree from MIT, a previous job at Google, a recommendation from a friend or colleague—and more on simple notions: How well does the person perform? What can the person do? And can it be quantified?
The technology is the product of Gild, the 18-month-old startup company of which Bonmassar is a co-founder. His is one of a handful of young businesses aiming to automate the discovery of talented programmers—a group that is in enormous demand. These efforts fall into the category of Big Data, using computers to gather and crunch all kinds of information to perform many tasks, whether recommending books, putting targeted ads onto websites or predicting health care outcomes or stock prices. Of late, growing numbers of academics and entrepreneurs are applying Big Data to human resources and the search for talent, creating a field called workforce science.
Gild is trying to see whether these technologies can also be used to predict how well a programmer will perform in a job. The company scours the Internet for clues: Is his or her code well-regarded by other programmers? Does it get reused? How does the programmer communicate ideas? How does he or she relate on social media sites?
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