AI Resume Screening & Skill Match System

Problem statement

Recruiters manually screen hundreds of resumes, often missing good candidates due to fatigue or time constraints. There is a need for an automated system that can evaluate resumes quickly and consistently.

Abstract

The system extracts text from PDF resumes, identifies key skills, work experience, and educational details using NLP models, and compares them with job descriptions. A similarity score is calculated using BERT or TF-IDF. The UI displays candidate ranking, strengths, and missing skills.

Components required

• Python
• spaCy / NLTK
• BERT / SentenceTransformers
• PDFMiner / PyMuPDF
• React or basic HTML UI

Block diagram

Working

The user uploads a PDF resume. Text is extracted and analyzed by NLP models to identify skills and experience. The job description is also processed. A similarity algorithm matches resume content to job requirements, producing a match score. Recruiters can view top candidates based on ranking.

Applications

• HR recruitment
• University placement cells
• Job portals
• Freelancer platforms