AI-Resume-Screening-System

AI Resume Screening System – Project Description

The AI Resume Screening System is an intelligent recruitment automation application designed to simplify and improve the process of screening job applicants. The system allows recruiters to upload multiple resumes in formats such as PDF, DOCX, and TXT and provide a Job Description (JD) for a specific position.

The system uses Natural Language Processing (NLP) and Machine Learning techniques to extract and analyze the content of resumes. It identifies relevant skills, compares the candidate's resume with the job description using TF-IDF and Cosine Similarity, and calculates a skill-matching score based on the required skills.

A final candidate score is generated by combining the AI-based resume similarity score and the skill-matching score. Based on the final score, candidates are categorized as Strong Match, Moderate Match, or Low Match. The system then ranks all applicants and displays the most suitable candidates for the given job role.

The application is developed using Python and Streamlit, with libraries such as Scikit-learn, Pandas, NumPy, PyPDF, and python-docx. The system provides recruiters with a user-friendly dashboard to view candidate rankings, matched skills, experience, similarity scores, and recommendations.

The main objective of this project is to reduce manual resume screening time, improve the efficiency of candidate shortlisting, and provide a consistent data-driven approach to recruitment. The system can be further enhanced using advanced NLP models such as BERT or Sentence Transformers, automated education and experience extraction, and an explainable AI-based candidate evaluation system.