This project demonstrates how Machine Learning can be applied to predict employee attrition and estimate its financial impact on the business.
The objective is to help HR teams identify employees at risk of leaving and estimate the potential cost of attrition.
Synthetic HR dataset including:
- salary
- engagement score
- performance score
- tenure
- department
- promotion history
- Data exploration
- Data preprocessing
- Machine learning model for attrition prediction
- Risk segmentation
- Business impact estimation
The model identifies employees with high attrition risk (>60%).
If these employees leave the company, the estimated replacement cost could reach 10.46 million €.
If HR interventions retain 30% of these employees, the organization could avoid approximately 3.14 million € in losses.
- Python
- Pandas
- Scikit-learn
- Matplotlib
- People Analytics