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An intelligent system that uses NLP and machine learning to automatically screen, parse, and rank resumes based on job requirements. Features keyword extraction, skill matching, and bias-free candidate scoring with a recruiter dashboard.
Problem Statement
Manual resume screening is time-consuming, inconsistent, and often biased. HR teams spend hours reviewing hundreds of applications for a single position, leading to delayed hiring and potentially overlooking qualified candidates.
Objectives
Parse and extract structured data from resumes in PDF/DOCX formats
Implement NLP-based skill matching against job descriptions
Build an unbiased candidate ranking algorithm
Create a recruiter dashboard with filtering and analytics
Generate automated shortlist reports
Modules
Resume Parser
Extract text, skills, education, and experience from uploaded resumes using NLP.
Job Description Analyzer
Parse job requirements and extract required skills, experience levels, and qualifications.
Matching Engine
Score and rank candidates based on skill overlap, experience, and job fit using ML models.
Recruiter Dashboard
Web interface for viewing rankings, filtering candidates, and managing job postings.
Report Generator
Automated PDF reports with candidate comparisons and hiring recommendations.
Expected Output
A web application where recruiters can post job descriptions, upload bulk resumes, and get AI-ranked candidate lists with match scores and detailed comparison reports.
Future Scope
Integration with LinkedIn API, video interview scheduling, chatbot for candidate queries, and predictive analytics for employee retention.