This report investigates an advanced Resume Analyzer that employs Natural Language Processing (NLP) to streamline the candidate screening process. Utilizing sophisticated algorithms, the system extracts pivotal information from resumes, such as skills and experience, and employs machine learning model for precise job relevance categorization. The architectural framework encompasses essential stages, including data preprocessing, feature extraction, and model training. Evaluation results underscore the system’s accuracy and scalability, with detailed case studies illustrating its practical applicability. The Resume Analyzer is positioned to revolutionize conventional recruitment processes, presenting a tool that enhances objectivity and facilitates more informed hiring decisions in today’s competitive job market.