VM JD Matcher – Resume vs JD Intelligence

Project Overview

VM JD Matcher is a GenAI‑powered application that evaluates how well a resume aligns with a job description. By combining skill extraction, semantic embeddings, and transformer‑based similarity scoring, the system provides a match percentage, highlights overlapping and missing skills, and delivers role‑specific guidance for jobseekers and recruiters.

Key Features

• Upload .docx resume and job description files.
• Automatic text preprocessing and normalization.
• Skill extraction using regex + custom skill dictionary.
• Semantic embeddings via Hugging Face all‑MiniLM‑L6‑v2.
• Cosine similarity to compute match score (%).
• Overlap vs missing skill analysis using Python set operations.
• Role‑based guidance for jobseekers and recruiters.
• Interactive bar and pie charts for visualization.
• Clean, user‑friendly UI built with Streamlit.

Tech Stack

• Python (core logic, preprocessing, set operations)
• Streamlit (UI + deployment)
• Hugging Face / Sentence‑Transformers (semantic embeddings)
• Regex (skill extraction)
• Matplotlib / Seaborn (visualizations)
• python‑docx (document parsing)

Impact

• Empowers jobseekers to tailor resumes with precision.
• Helps recruiters quickly identify candidate fit.
• Improves hiring efficiency through automated skill matching.
• Demonstrates practical use of GenAI in recruitment workflows.

Key Insight Summary

VM JD Matcher shows how transformer embeddings + skill extraction can produce accurate, actionable resume‑to‑JD alignment. The system blends GenAI reasoning with practical HR analytics to deliver a modern recruitment intelligence tool.

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