San Francisco start-up Bright Media Corporation Inc. is unveiling its debut product today that it says will bring big data analytics to the process of matching jobs with people, cutting down on the frustration experienced by job seekers and hiring managers.
Founded in 2010, Bright is also announcing a $6 million Series A million fundraising round led by angel investors including hedge fund executive John Burbank. The financing round was actually completed six months ago. Chief Executive Steve Goodman said in an interview that he plans to raise additional financing this fall, probably in the $15 million range, at which point the 20-person company will likely hire 60 more employees, with an emphasis on engineering and data science.
The company's jobs site, which is available to the public beginning today, eliminates the "search" in job seeking. After uploading a resume and filling out profile information, the site automatically generates job postings for which the user is qualified. The site gives the user a score ranging from 1 to 100 for how qualified the candidate is for each job. Hiring managers will be able to rank applicants according to these scores. They will also see scores of candidates who looked at or began to fill out a job posting but did not complete it.
The company's scoring algorithm is based on data analysis of 8.6 million job seeker profiles, 2.8 million resumes and 13,400 job descriptions. Around 75% of the company's 20-person staff is comprised of engineers and data scientists who have spent the past two years crunching the data to parse out new insights about what makes a candidate a good fit for a job.
Recruiters look for matches between keywords in resumes and job descriptions. Yet, the reasons that hiring managers ultimately choose who to hire often have little to do with keywords. For instance, the Bright engineering team discovered through their analysis that Microsoft is much more likely to hire engineers from VMware than from Cisco, regardless of how well keywords match.
The company's algorithm also takes into account factors such as an applicant's career progression, certification and employment patterns. Users are differentiated based on the hiring preferences of the company they're applying to.
"You can have two job descriptions that are exactly the same from General Motors and Ford, and your Bright Score will be different because GM looks for different things than Ford does," said Goodman.
Goodman says that the company's technology will help solve one of the job market's most vexing problems: an oversupply of job applicants that leads to unqualified job seekers flooding recruiter inboxes with resumes, what Goodman calls a "spray and pray" strategy. That leads recruiters to skim quickly through resumes to look for keywords listed in the job description. However, many job descriptions are poorly written and don't include the right hiring criteria, Goodman said.
"What the hiring manager wants and what the recruiter is looking for are off, and they're off by a lot," Goodman said.
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