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---
language: en
license: mit
pipeline_tag: text-classification
tags:
- resume
- ats
- pii
- nlp
- huggingface
---
# 🤖 Resume PII Masking & ATS Optimizer
A professional-grade NLP pipeline to automatically **detect and mask Personally Identifiable Information (PII)** in resumes and **evaluate resume quality based on Applicant Tracking System (ATS) scoring**. Built using the Hugging Face Transformers ecosystem and fine-tuned with custom data, this project simulates real-world applications of Natural Language Processing in HR tech and recruitment automation systems.
---
## Key Features
| Feature | Description |
|-------------------------------|----------------------------------------------------------------------------|
| PII Masking | Detects and masks names, emails, phone numbers, and addresses using NER. |
| Resume Parsing | Handles large resumes (up to 2000+ words) with tokenizer support. |
| ATS Resume Optimization | Scores resumes based on keyword density, formatting, and clarity. |
| Job Description Matching | Optional feature to match resumes with specific job descriptions. |
| Hugging Face Integration | Fine-tune and deploy models directly on Hugging Face Hub. |
| Modular Architecture | Well-organized, scalable, and production-ready codebase. |
---
## 📁 Folder Structure
```bash
resume_ats_project/
├── data/ # Contains resume samples and PII-labeled training data
│ ├── resumes.json
│ └── pii_train.json
├── models/ # Directory to save fine-tuned models
│ └── ats_model/
├── resume_parser.py # Tokenization, segmentation, and formatting
├── pii_trainer.py # Script to fine-tune NER model
├── optimizer.py # ATS scoring logic
├── infer.py # Combines parsing, masking, and optimization
├── app.py # (Optional) Flask or Gradio interface
├── requirements.txt
└── README.md
---
Installation
git clone https://github.com/your-username/resume-ats-optimizer.git
cd resume_ats_optimizer
pip install -r requirements.txt
---
Real-World Applications
This project mimics systems used by:
LinkedIn Talent Solutions (Resume scoring + redaction)
Amazon HR Automation (Internal resume screening tools)
Google Cloud AutoML NER for internal document pipelines
Infosys & TCS resume filtering portals
---
You can adapt it to:
Job matching portals
Candidate anonymization systems
Large-scale recruitment automation tools
---
License
Licensed under the MIT License.
---
Author
Karthikeyan M C
karthikeyanmc1925@example.com
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