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PythonCapstone Project
Bank Customer Churn Analysis & Risk Scoring
BK
BUILT BYBilal Khan
BEFOREOperations Officer
→
OUTCOMEData Analyst at Habib Bank
Status: Live DeployedInteractive Live Demo (Sandbox)→
Project Overview
A Python-driven analytical project using Pandas and Seaborn to pinpoint why high-value credit card holders were leaving.
Data Scrubbing & Cleaning Pipeline
The student imported raw messy CSV database backups, scrubbed redundant column entries, normalized data structures, handled duplicate records, and configured relationship models using SQL schemas and Power BI.
Analytical Insights Generated
Configured cohort retention models, isolated regional operational leakages, tracked active customer churn risk, and mapped average revenue metrics across locations.
Project Specs
CORE TOOLPython
DATA ROWS PROCESSED500,000+ Records
TIME TO BUILD3 Weeks
COMPLEXITY LEVELHiring Grade