🤖 TalentLens AI

AI-Powered Resume Intelligence Platform that ranks candidates using semantic matching, career progression, skill analysis, behavioral scoring, and experience evaluation.

🚀 TalentLens-AI

AI-Powered Resume Intelligence Platform for Explainable Candidate Ranking

TalentLens-AI is an AI-powered resume screening platform that helps recruiters identify the most suitable candidates by combining Natural Language Processing (NLP), semantic similarity, and explainable AI scoring.

Instead of relying only on keyword matching, TalentLens-AI evaluates resumes using multiple intelligent modules including semantic understanding, career progression, technical skills, behavioral analysis, and professional experience to generate a transparent 100-point candidate score.

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🚀 TalentLens-AI

AI-Powered Resume Intelligence Platform for Explainable Candidate Ranking

TalentLens-AI is an AI-powered resume screening platform...

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📸 Dashboard Preview

Dashboard

Top Candidates

Analytics

🌟 Key Features

• 🤖 Semantic Resume Matching using Sentence Transformers
• 📈 Career Progression Analysis
• 🛠 Skill Matching Engine
• 🧠 Behavioral Analysis
• 💼 Experience Evaluation
• 📊 Explainable 100-Point AI Scoring
• 🏆 Intelligent Candidate Ranking
• 📋 Interactive Streamlit Dashboard
• 📥 CSV Export for Recruiters

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🎯 Why TalentLens-AI?

Traditional resume screening is manual, time-consuming, and often biased toward keyword matching.

TalentLens-AI introduces an explainable AI-based ranking framework that evaluates candidates from multiple perspectives rather than relying solely on resume keywords.

The platform intelligently combines:

• 🔍 Semantic Resume Matching
• 💼 Career Progression Analysis
• 🛠 Technical Skill Matching
• 🧠 Behavioral Assessment
• 📈 Experience Evaluation

These independent AI modules are combined using a weighted scoring engine to generate an explainable 100-point ranking, helping recruiters make faster and more informed hiring decisions.

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🏛 System Architecture

                   Job Description
                          │
                          ▼
                  Candidate Resumes
                          │
                          ▼
               Resume Processing Engine
                          │
                          ▼
 ┌───────────────────────────────────────────────────────┐
 │                                                       │
 │  Semantic Matching                                    │
 │  Career Progression Analysis                          │
 │  Skill Matching                                       │
 │  Behavioral Analysis                                  │
 │  Experience Evaluation                                │
 │                                                       │
 └───────────────────────────────────────────────────────┘
                          │
                          ▼
              Weighted AI Scoring Engine
                          │
                          ▼
             Explainable 100-Point Score
                          │
                          ▼
             Candidate Ranking & Sorting
                          │
               ┌──────────┴──────────┐
               ▼                     ▼
      Streamlit Dashboard      CSV Export

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🏆 AI Scoring Framework

Each candidate is evaluated using five AI-powered scoring modules.

Component	Weight
Semantic Matching	40%
Career Progression	20%
Skill Matching	15%
Behavioral Analysis	15%
Experience Analysis	10%

Final Candidate Score = 100 Points

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📂 Project Structure

TalentLens-AI
│
├── data/
├── docs/
├── outputs/
├── src/
├── tests/
│
├── app.py
├── rank.py
├── requirements.txt
├── README.md
└── .gitignore

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⚙️ Technology Stack

Programming

• Python

Artificial Intelligence

• Sentence Transformers
• Hugging Face Transformers
• NLP

Data Processing

• Pandas
• NumPy
• Scikit-learn

Frontend

• Streamlit

Version Control

• Git
• GitHub

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🚀 Installation

Clone the repository

git clone https://github.com/souvikpal77/TalentLens-AI.git

Move into the project folder

cd TalentLens-AI

Install dependencies

pip install -r requirements.txt

Launch the application

streamlit run app.py

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📊 Sample Ranking Output

Rank	Candidate ID	AI Score
🥇 1	CAND_0000021	100.00
🥈 2	CAND_0000002	94.78
🥉 3	CAND_0000045	87.65
4	CAND_0000041	87.26
5	CAND_0000017	73.24

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🔄 Project Workflow

1. Load Job Description
2. Load Candidate Resumes
3. Resume Preprocessing
4. Semantic Similarity Analysis
5. Skill Matching
6. Career Progression Analysis
7. Behavioral Scoring
8. Experience Evaluation
9. Weighted AI Scoring
10. Candidate Ranking
11. Dashboard Visualization
12. CSV Report Generation

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💡 Future Enhancements

• 📄 PDF Resume Parsing
• 🖼 OCR-Based Resume Extraction
• 🤖 LLM-Powered Resume Feedback
• 🎯 Interview Recommendation Engine
• 📊 Recruiter Analytics Dashboard
• ☁ Cloud Deployment
• 🔗 REST API Support
• 🌐 Multi-language Resume Support

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📌 Dataset

The original candidates.jsonl dataset is excluded from this repository because it exceeds GitHub's file size limit.

The repository includes sample data required to demonstrate the complete workflow.

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👨‍💻 Developer

Souvik Pal

Artificial Intelligence • Machine Learning • NLP • Python Developer

GitHub: https://github.com/souvikpal77

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📜 License

This project is developed for educational, research, and hackathon purposes.

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⭐ Support

If you found this project useful, consider giving this repository a ⭐ on GitHub.

It motivates future development and improvements.