Employee Attrition Leading Factors

As part of the Operations Research Data Analytics course, my team and I conducted an in-depth analysis of employee attrition using HR data sourced from Kaggle. The project aimed to identify key characteristics contributing to employee turnover and support strategic workforce planning 👩🏻‍💻👨🏻‍💻.

- Cleaned and preprocessed a snapshot dataset of employee records, addressing missing values, encoding categorical variables, and removing inconsistencies.
- Explored demographic, job-related, and satisfaction-based features using summary statistics and visualizations to understand attrition trends.
- Applied logistic regression to model the likelihood of attrition across the entire dataset and within individual departments.
- Identified high-risk profiles based on age, job satisfaction, years at company, and workload factors.
- Found department-specific drivers of attrition, enabling targeted retention strategies.
- Recommended personalized retention interventions and proactive HR policies to improve employee engagement and reduce turnover.

Through this project, I strengthened my ability to apply regression modeling and data preprocessing techniques to real-world business problems. It enhanced my understanding of how data-driven insights can inform human capital strategy and operational decision-making.