RESUME SCREENING SYSTEM REVOLUTIONIZING TALENT ACQUISITION THROUGH DATASCIENCE

Abstract

In today’s competitive job market, organizations receive thousands of resumes for a single job role, making manual resume screening time-consuming, costly, and prone to human bias. To overcome these challenges, this paper proposes an intelligent Resume Screening System powered by Data Science and Machine Learning techniques. The system automatically analyzes, filters, and ranks resumes based on job requirements such as skills, experience, and qualifications. Natural Language Processing (NLP) techniques are used to extract relevant information from resumes, while machine learning algorithms help in matching candidates to suitable job profiles. This approach improves recruitment efficiency, reduces hiring time, and ensures fair candidate evaluation. The proposed system revolutionizes talent acquisition by enabling faster, accurate, and unbiased resume screening.