Understanding Job Requirements Using Natural Language Processing

With the rising number of remote jobs and mediums on which companies rely as funnels to attract job candidates, the number of job applications receives increases exponentially over time. Human Resource (HR) departments are becoming bottlenecks for pleasant applicant experiences because of the laboriousness of the application processing task. Increasing the size of HR departments works to a certain point but hiring more HR specialists becomes impossible from a financial and managerial standpoint. We propose a novel approach for candidate filtering based on competence matching between job ads created by companies and submitted resumes. The proposed system achieves 99.5% accuracy and relies on natural language processing techniques to extract information from both candidates' resumes and job ads. It allows companies to create their personalized automated filters using the extracted information.