AI4HR Recruiter: a job recommender system for internal recruitment in consulting companies

Abstract

Recruiting job candidates is a crucial activity for consulting companies to fulfill their consulting activities for customers or internal projects. Due to the complexity of the recruitment process, companies adopt standardized resume formats to be able to identify or compare candidates. However, this process requires significant involvement from human resource specialists and project leaders. In this paper, we present AI4HR Recruiter, a recommender system designed to improve the internal recruitment process of consultants. The system uses artificial intelligence-based techniques, specifically pre-trained sentence transformers. It aims at supporting recruiters in identifying and selecting candidates, rather than automating the process. We measure improvement in efficiency in terms of gains in recruiters time induced by the recommendation explanation presence. We also measure the impact on users’ satisfaction of two different types of algorithm to generate recommendations. To do so, we have been conducting a two fold study in a real-life setting for six months, where on the one hand, telemetry data was gathered while recommendation process user interaction was being performed and on the other hand, surveys about users’ satisfaction were conducted afterward. Our results evaluation demonstrates the effectiveness of the system in assisting recruiters in candidates selection process.