How Indeed uses AI to find people jobs

The robots are coming for your jobs, experts say. But no matter if you’re a Luddite or an engineer at Microsoft, as the AI age threatens the livelihood of many, services like Indeed that help people find work may be the kind of AI everyone can agree on. Indeed VP Raj Mukherjee said one big improvement […]

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The robots are coming for your jobs, experts say. But no matter if you’re a Luddite or an engineer at Microsoft, as the AI age threatens the livelihood of many, services like Indeed that help people find work may be the kind of AI everyone can agree on.

Indeed VP Raj Mukherjee said one big improvement fueled by AI has been analysis of job descriptions and applicant resumes with natural language processing (NLP) to better match candidates with the sorts of jobs they’re qualified to do.

“You’ll certainly start to figure out what are the core requirements of this job, so when I’m a job seeker, when I look at a job description it may say ‘Your resume is a match,'” he said.

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This application of NLP has increased the amount of employers responding back to job applicants 10 percent across all industries and 15 percent in tech, Mukherjee said at VB Summit.

Other ways AI shapes job searches on Indeed include the personalized results a job seeker sees when they get an email or search the site, and regression techniques used to ferret out fraudulent job applications.

AI was also used to predict salary price ranges for job applicants, but this service was nixed after employers said the Indeed prediction was actually below what they were willing to pay.

“That’s an example of a misstep, and a great learning for us,” Mukherjee said. Indeed has stopped serving up salary predictions for some jobs today, but continues its work in this area using 450 million salary data points collected from former employees and job descriptions.

In the future, Indeed may use AI as a way to get more people to in-person job fairs, Mukherjee said, and invest more in exploration of sentiment analysis NLP to get an idea of how happy employees are as a Google engineer or Walmart cashier.

Data for sentiment analysis will come from 15 million reviews of companies by former employees.