Hidden Diamonds: Using Skill Mapper to Find Compatible Talent
The fruits of innovation in machine learning have barely reached the talent industry, much less recruiting teams. According to the Wall Street Journal, approximately 90% of companies use an Applicant Tracking System (ATS) that parses applicants’ resumes, extracts information and makes its content searchable. These tools, however, rely mainly on keyword search to initially filter through applicants .
As a result, the majority of compatible applicants may fall through the cracks if they do not have the exact keyword that the recruiter inputs. We empathize with talent acquisition teams — assessing skills for each position is an arduous task. The ATS’s lack of optimization in their parsing and skill mapping greatly reduces the amount of sourced applicants, putting both the companies and applicants at a disadvantage. Atipica’s core technologies address this problem by moving beyond simple keyword search.
We recently improved Skill Mapper — a machine learning model that predicts relevant skills given a skill or a job title.
Let’s take the example of Company X. They are hiring a data scientist with experience in natural language processing. They have two candidates. — Candidate A and Candidate B.
With keywords such as “natural language processing” and “data scientist”, Candidate A is more likely to be overlooked by the ATS search capability.
Atipica’s Skill Mapper detects the most relevant skills for the job. In effect, the search space is augmented, and compatible applicants are less likely to fall through the cracks, resulting in a higher number of compatible applicants that your recruiter can vet.
For instance, below is a skill map of natural language processing, a skill commonly sought out in data scientists and used as a keyword during a typical search.
Skill Mapper works equally well across different industries. Below is a skill map of genomics.
And finally, Skill Mapper is not limited to just technical skills. As an extreme case, if Instagram were a skill, these would be its most relevant skills:
Our end goal is not to eliminate humans from the recruiting process — but to simply provide talent acquisition teams with tools that makes the process more efficient and equitable. We believe that tools such as Atipica Matching are a step in the right direction. If you’d like to learn more, shoot us a message.
NEXT UP: GENDER SKILL CLUSTERING
In our next post, we will use Skill Mapper to understand the differences in skill-set between males and females as they move through the funnel, and how that affects their chances of getting hired. Stay tuned!