• Performed data cleaning, transformation, and feature engineering to implement the Logistic Regression model for a binary prediction with a 10-fold cross-validation score of 92% • Segmented the customers into clusters based on Age, Spending score, and Balance using the KMeans clustering algorithm • Modeled customer retention metrics such as retention, churn, and customer loyalty rate with an average uplift of 8% • Deployed a streamlit machine learning app and prepared tableau BI report to identify new business opportunities