Matching and scoring

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HireHunt provides employers with an array of options to automate the scoring and ranking for incoming applicants to your jobs.

This document outlines the capabilities and limitations of the HireHunt scoring system.

HireHunt uses a combination of AI-powered scoring with your own customizations that you have added for each job, described below in the ‘Measurable factors’ section.

On the other hand, there are sometimes requirements that cannot be measured due to the fact that they are ‘subjective’ factors that cannot be unbiasedly quantified and would require human review.

What are the measurable factors that HireHunt uses to show matching scores and rank applications?

AI smart matching

If the job title is one of the AI-powered titles on HireHunt:

The system generates and understands over 1,500 job based on linguistic analysis of profiles. Based on them, the system scores the relevancy of their profile to the job (i.e. 78% relevancy) as compared to thousands of samples of qualified applicants, beyond the basic keywords.

Similar to how AI can map out and identify your face features for facial recognition, HireHunt maps out the linguistic profiles as related to job titles in order to determine relevancy with a high degree of accuracy.

As with any machine learning algorithm, the accuracy is not 100%. However, HireHunt employs a feedback mechanism that continuously optimizes the algorithm based on your interactions to learn and achieve higher accuracy for you the more you interact with talents.

Qualifying questions

Extra elements based on answers to qualifying questions provided through the application.

Example:

– Do you have a master’s degree? (‘Yes’ answer qualifies applicant, ‘No’ answer disqualifies)

Skills Assessment Scores

The system scores the answers based on the multiple choice selections, you can select the weight by adjusting the points assigned to that question.Quantifiable scores for required skills that are system identified and supported.

If you have selected a required skill in the job application and added an assessment, their score based on completing that MCQ assessment will factor in the matching score.

Job Description Keywords

Any Keywords related to the job description and the attached documents (CVs) are used as part of the relevancy scores.

The system also scores the CV based on the mutual words that are found in the job description that you have added.

What are the subjective factors that are not supported by HireHunt?

A. The applicant speaks “like a native speaker”.

The system cannot identify the language fluency through a voice message as it is not something that is machine based. It can evaluate language skills through written answers only. The voice answers can be used as a supportive screening method to organically filter confident speakers and to reduce phone screening calls.

B. The applicant has a “good background”.

The system cannot identify whether the applicant/ CV on the database has a good background or not. Requirements such are this differ greatly from company to company. The best way is to set the questions that can help you decide this, and if they can be qualifier questions with specific answers, then that factor can be factored into the automated relevancy ranking.

C. The applicant comes from a “specific company in a related industry”.

Example: Companies who are related to the manufacturing industry only.
The system cannot identify which market industry these companies are from. It identifies the related field but cannot measure the company’s industry if it is not clearly written in the CV.

HireHunt advises all recruiters and employers to reduce the amount of subjective factors as much as possible, to convert them into quantifiable factors as shown above. This is a good exercise in and of itself so that the scoring of applicants can be consistent, fair and with as little bias as possible.