AI-Driven Candidate Evaluation and Screening System for Intelligent Recruitment

Abstract

Thousands of job applications must be analyzed throughout recruitment processes in contemporary businesses, which makes manual screening ineffective and biased. Artificial Intelligence (AI) provides automated solutions that enhance candidate evaluation's accuracy, efficiency, and fairness. In order to automatically assess resumes, match skills with job descriptions, and rank candidates, this paper proposes an AI-Driven Candidate Evaluation and Screening System that makes use of Natural Language Processing (NLP), Machine Learning (ML), and predictive analytics. To forecast candidate suitability, the suggested methodology combines resume parsing, feature extraction, similarity computation, and classification models. Improved screening effectiveness and shorter recruitment times are shown via experimental evaluation. The solution offers businesses sophisticated and scalable hiring assistance.