Using machine learning to match job candidates

Using machine learning to match job candidates

Using machine learning to match job candidates

Global staffing firm leverages machine learning to automate matching of candidates with jobs

 

At a Glance:

To retain their competitive edge and respond to job openings more quickly than other agencies, a global staffing firm needed to automate the process of matching candidates with opportunities that match their skills. That’s why they contacted us.

 

Customer Challenge

When an employer publishes a new job opening, employment agencies race to be the first to put qualified candidates in front of the hiring manager. As more competitors enter the market, firms are under increased pressure to deliver the most qualified candidates as quickly as they can in response to client requests

 

Every day our client receives a feed of candidates from each of their locations around the world. To match these candidates with job opportunities, they used a Drupal search function that analyzed keywords in candidate skills and job titles. They needed a more sophisticated system that could incorporate location, previous job titles, years of experience performing certain functions, and other factors to improve their competitive advantage.

 

Why They Chose Us

We had been working with this client for over 10 years and completed more than 100 successful projects for them. Our client knew we possess both the technical expertise and the business process knowledge to be able to develop and implement the right solution to meet their needs, on time and on budget.

 

Value and Benefits - “The Wins”

We designed and implemented a new system using machine learning to automate the matching of candidates with job opportunities. We vectorized the skills of every candidate in the system and implemented a process for vectorizing new candidates’ skills as they come on board. When a job notice arrives, the system compares the job’s requirements with the candidate skills to quickly find the appropriate candidates.

 

Using this machine learning model as a basis, we created several matching systems:

  • Candidate match engine: The system identifies the top five jobs for each candidate based on job requirements and automatically sends them to the candidate via email.
  • Availability matching: Candidates who are already working for the staffing firm but who will soon be available also receive emails with their top job matches.
  • Anniversary engine: Automated emails go to companies the firm had worked with in the past highlighting the candidates they have available whose skills match the client’s past needs.

As a result of the new matching system, our client can fill job opportunities more quickly and accurately by finding the right candidates, which improves client satisfaction in addition to benefiting their bottom line.