Hired by an algorithm: Entelo gets $3.5M to expand data-based recruiting

Workers in fields like technology and academia are posting more information about their professional lives online, creating a pool of public data that can be machine-sifted to find job candidates.

That’s the idea behind Entelo, a start-up that believes algorithms can replace much of the heavy lifting performed by recruiters and HR departments. The San Francisco-based company, whose clients include Yelp(s yelp) and Square, parses millions of data points to create what amounts to a “professional graph” for thousands of skilled employees.

As my colleague Derrick Harris explained, Entelo’s data-aggregation software combs through sites like Github and LinkedIn(s lnkd) to find job candidates who are likely to be not just qualified, but also available (a burst of online activity is one of the strongest signals someone is ready to move).

Entelo now has over 80 paying clients and ten full-time employees, and on Wednesday it announced a $3.5 million funding round led by Battery Ventures with the participation of Menlo Ventures. The company will use the cash to expand its engineering operations and, eventually, to push into new professional verticals beyond tech.

In a phone interview, CEO Jon Bischke explained: “The recruiting industry is broken because some people don’t know companies are looking to hire them while others are being constantly being bothered by recruiters when they don’t want to move.”

Bischke says Entelo’s value is easy to demonstrate to clients because they can simply contrast its ROI versus other forms of recruiting. As for pricing, the company rejects the “pay for success” model typically used by head-hunters; instead, it charges clients $6,000 per license to use its search engine and predictive analytics tools.

The most intriguing part of Entelo’s business may be its potential for expansion to different professions. Bischke says the company’s next vertical will be academia because professors are creating large pools of public data about themselves on sites like ResearchGate and Academia.edu. He also predicts that algorithm-based hiring will eventually become part of most white collar professions.