AI Resume Screener

What It Does

The AI Resume Screener is designed to automate the initial stage of the hiring process. It extracts text from multiple resumes (supporting .docx format) and compares them against a target job description to rank candidates by relevance.

Core Methodology

• TF-IDF Training: Learned on a corpus of professional documents to identify key skills and terminology.
• Cosine Similarity: Measures the mathematical distance between the resume vector and the job description vector to calculate a "match percentage".
• Skill Overlap Analysis: Identifies specific tech stacks and keywords present in both the candidate's profile and the requirement.
• Dynamic Classification: Automatically labels candidates as Fit, Maybe, or Reject based on configurable similarity thresholds.

Key Functionalities

• Batch processing of directory-hosted resumes.
• Support for modern document formats through python-docx.
• Clean CLI output with sorted rankings and match scores.

Stack & Architecture

• Python
• scikit-learn
• python-docx
• TF-IDF Vectorization
• Cosine Similarity