International Journal of Scientific Research and Engineering Development

This document The large number of resumes received for a single job opening makes manual screening difficult for recruiters. Reviewing every application takes considerable time, and important candidates can sometimes be missed when screening depends mainly on keywords. This paper presents an Automated Resume Screening System that uses Natural Language Processing (NLP) to analyse resumes and compare them with job descriptions. The system extracts information such as skills, qualifications, certifications, and experience from resume documents. TF-IDF and cosine similarity are then used to measure how closely a candidate profile matches a given job description. An ATS scoring component combines the matching information and provides a suitability score along with suggestions for improving the resume. A Flask-based dashboard allows the results to be viewed in a simple interface. The experimental results show that the system can improve the speed and consistency of resume screening while helping recruiters identify candidates whose profiles are more closely related to the requirements of a job.

Anjaneya, Channabasappa S L, "Automated Resume Screening System Using NLP for Smart Hiring Decisions" International Journal of Scientific Research and Engineering Development, V9(4): Page(1486-1489) July-August 2026. ISSN: 2581-7175. www.ijsred.com. Published by Scientific and Academic Research Publishing.