This project deals with the segmentation and grouping of the bank credit card customers using UnSupervised K-Means Clustering Algorithm. The project involves below steps in the life-cycle and implementation. 1. Data Exploration, Analysis and Visualisations 2. Data Cleaning 3. Data Pre-Processing and Scaling 4. Model Fitting 5. Model Validation using Performance Quality Metrics namely WCSS, Elbow Method and Silhouette Coefficient/Score 6. Optimized Model Selection with appropriate number of clusters based on the various Performance Quality Metrics 7. Analysis Insights and Interpretations of 2 different business scenarios with various Visualisations