JOYBOY_07 Ranker | Intelligent Candidate Discovery

This repository contains the JOYBOY_07 Ranker, a multi-stage cascading pipeline engineered for the Redrob Talent Intelligence Challenge.

🚀 Live Sandbox

Access the Command Center

🏗 System Architecture

Our engine is designed to operate under strict CPU-only constraints while aggressively filtering for dataset traps.

1. Deterministic Guardrails: Hard-filters honeypots and "keyword stuffers" (e.g., non-engineering titles with high skill keywords).
2. Hybrid Retrieval: Uses optimized TF-IDF sparse matching to prune 100k candidates to the top 2k, followed by dense semantic scoring for relevance.
3. Behavioral Calibration: Applies a mathematical multiplier to prioritize candidates with high recruiter response rates and recent platform activity.

🛠 Tech Stack

• Backend: Python, Scikit-Learn (TF-IDF), Pandas, NumPy.
• Frontend: Streamlit with custom Glassmorphism CSS and Plotly-integrated visualizations.
• Performance: Optimized for <5 minute execution on CPU-constrained environments.

📋 How to Reproduce

1. Clone the repository: git clone https://github.com/07MADARA/talent-ranker
2. Install dependencies: pip install -r requirements.txt
3. Run the ranker: python rank.py (ensure candidates.jsonl is in the root directory).
4. Validate results: python validate_submission.py team_antigravity.csv

---

Submission by Team JOYBOY_07