Analyzing Warehouse Operational Efficiency - Capstone Project.
No two warehouses are the same—some excel at meeting demand with minimal delays, while others struggle with inefficiencies and disruptions. Management wants to understand what drives these differences and ensure consistent operational efficiency across all warehouses to support the FMCG business’s growth.
Operational challenges such as transport delays, storage limitations, and staffing shortages are impacting warehouse efficiency. Identifying these factors and addressing them is crucial to maintaining consistent performance.
Goal: SupplyFlow FMCG Solutions will perform a detailed analysis of historical warehouse performance data to uncover the key factors affecting efficiency. A model will be developed to provide actionable insights and recommend strategies for improving operations, infrastructure, and resource allocation in underperforming warehouses.
Customer Churn Prediction App
Built and deployed an end-to-end machine learning pipeline for predicting customer churn. This project demonstrates skills in data preprocessing, model training (Scikit-Learn), and building an interactive web application with Streamlit. The final app supports both single- and batch-predictions, showcasing a full-stack data science workflow.
Learned to troubleshoot model export/import errors and optimize a production-ready application. This project is a testament to problem-solving and persistent iteration.
E-commerce Demand Forecasting & Analysis
A data science project showcasing an end-to-end solution for demand forecasting. The project demonstrates proficiency in time-series analysis (Prophet), scalable pipelines, rigorous backtesting, and building interactive, shareable dashboards with Streamlit.
📊 Customer Churn Prediction
"End-to-End Machine Learning project predicting customer churn with Python, Pandas, Scikit-learn, and XGBoost.”
