RetentionLens: HR Analytics

Project Overview

This project implements an HR analytics solution to quantify and reduce the financial impact of employee attrition. Using data science and machine learning techniques, the project aims to:

1. Quantify the full financial impact of employee attrition
2. Identify at-risk employees before they leave
3. Determine key drivers of turnover
4. Recommend targeted interventions with measurable ROI

Project Structure

The project follows a modular structure:

• notebooks/: Jupyter notebooks for exploration and development
• src/: Source code modules for data processing, modeling, financial analysis, and visualization
• data/: Data storage (raw, processed, and models)
• docs/: Project documentation
• streamlit/: Streamlit dashboard application

Setup Instructions

Prerequisites

• Python 3.10 or higher
• Git

Installation

1. Clone the repository:

   git clone https://github.com/your-username/hr-attrition-analytics.git
   cd hr-attrition-analytics
   

2. Create a virtual environment:

   python -m venv venv
   source venv/bin/activate  # On Windows, use: venv\Scripts\activate
   

3. Install dependencies:

   pip install -r requirements.txt
   

Running the Application

To run the Streamlit dashboard:

cd streamlit
streamlit run app.py

Implementation Plan

The project implementation follows an 8-week plan:

• Weeks 1-2: Foundation & Data Preparation
• Weeks 3-4: Feature Engineering & Modeling
• Weeks 5-6: Financial Analysis & Prototype Development
• Weeks 7-8: Validation & Refinement

Documentation

For detailed information, see the documentation in the docs/ directory:

• Business Case
• Data Dictionary
• Model Methodology
• User Guide