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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM44548
Volume:
9 |
4 |
Apr 2025
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
This paper presents an AI-driven resume analyzer designed to streamline and enhance the job candidate assessment process. The system utilizes Natural Language Processing (NLP) techniques and machine learning algorithms to process and evaluate resumes efficiently. By extracting key information, calculating an ATS compatibility score, identifying grammar errors, and providing improvement suggestions, the analyzer aims to assist both job seekers and recruiters optimize the resume screening process. The platform also evaluates resumes against job-specific requirements and offers curated resources, to help users develop relevant skills and stay competitive in the job market. By automating the resume review process, the project enables job seekers to enhance their profiles, increasing their chances of success in todayâs dynamic hiring environment. Designed with scalability, accuracy, and user-friendliness in mind, this application serves as a valuable tool for job seekers, recruiters, and educational institutions. The system is implemented using Python, FastAPI for the backend, and Streamlit for a user-friendly interface.
KEYWORDS
Publication Date
4/14/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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