AI-POWERED RESUME SCREENING AND CANDIDATE RANKING SYSTEM USING NLP AND MACHINE LEARNING

The rapid growth of job applications in modern recruitment processes has made manual

resume screening increasingly inefficient, time-consuming, and susceptible to human bias. Orga-
nizations often receive hundreds or thousands of applications for a single position, making it chal-
lenging for Human Resource (HR) professionals to identify the most suitable candidates accurately

and quickly. To address these challenges, this project proposes an AI-Powered Resume Scanner—an
intelligent recruitment support system that leverages Artificial Intelligence (AI), Natural Language
Processing (NLP), and Machine Learning (ML) techniques to automate the resume evaluation and
candidate ranking process. The proposed system extracts and analyzes essential information from
resumes, including technical skills, educational background, professional experience, certifications,
and relevant keywords. Using NLP techniques, the system processes both structured and unstructured
resume formats to identify meaningful patterns and contextual information. It then compares the
extracted data with predefined job requirements and computes a compatibility or matching score for
each candidate using machine learning algorithms. Based on the calculated scores, the system ranks
candidates in order of relevance, enabling HR professionals to quickly shortlist the most qualified
applicants. This automated approach not only reduces screening time and operational costs but also
minimizes human bias, ensuring a more objective and data-driven hiring process. Furthermore, the
system can be implemented as a scalable web-based platform, allowing organizations to manage large
volumes of applications efficiently. Overall, the AI-Powered Resume Scanner enhances recruit-ment
efficiency, improves hiring accuracy, and supports better decision-making in talent acquisition
through intelligent automation and advanced data analysis techniques.