AI Resume Analyzer

The increasing adoption of Applicant Tracking Systems (ATS) has transformed the recruitment process by automating resume screening and candidate selection. However, many qualified candidates fail to pass ATS screening due to inadequate keyword optimization and poor alignment with job descriptions. This paper presents ResumeIQ, an intelligent resume analysis system that evaluates resumes using Natural Language Processing (NLP), keyword matching, and semantic similarity analysis. The proposed system extracts structured information from resumes, including skills, education, and work experience, and compares it with job requirements to calculate an ATS compatibility score. The system also identifies missing skills and provides personalized recommendations to improve resume quality. A web-based architecture using React.js, Node.js, Express.js, and MongoDB is implemented to support scalable resume analysis and recruiter-assisted candidate ranking. Experimental evaluation demonstrates that ResumeIQ improves recruitment efficiency by automating resume screening while providing transparent and explainable feedback to job seekers. The proposed framework offers a practical solution for intelligent recruitment and ATS optimization.