A new job board called Bright aims to kill resume overload with a little bit of data science.
Instead of encouraging candidates to apply for as many jobs as possible, Bright promises to cut down on unnecessary resume exchanges by showing both parties what is the best fit for them.
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To do so, the startup analyzed 2.8 million resumes submitted in response to more than 2.1 million job descriptions on its beta site. Hundreds of HR recruiters looked at the resumes and rated them based on compatibility with their corresponding descriptions.
Meanwhile, a team of about 15 data scientists and engineers tracked the ratings and used them to develop an algorithm that not only predicts such compatibility, but also learns more about a specific employer's preferences as that employer uses the site. Bright uses it to assign each job seeker a score for each job.
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Like competing job site Path.to, it feels a little like a dating site.
Job seekers can see their scores for each job while they're browsing the site. And even if they search for the wrong keyword, they'll be given jobs that fit their skills. If a landscaper searches for the word "engineer," for instance, Bright will turn up witty calls for "plant engineers" but leave out the jobs that require an engineering degree.
Hiring managers can sort submitted resumes by the same score applicants. They can also see applicants with high scores who viewed the job or started, but didn't complete, an application.
Where Path.to focuses on cultural fit, Bright's objective is strictly tied to the resume. But it's not always a matter where the applicant went to school and the last job they held, which are the two factors HR reps who participated in Bright's beta were most likely to look at.
Goodman cites an example where a company doesn't even mention within its job description the skill most of its hires have in common.
"They’re looking for the wrong stuff, and they’re putting the wrong people in the interviews," he says.
Image courtesy of iStockphoto, fotosipsak.
This story originally published on Mashable here.
