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1. credit-risk-analysis credit-risk-analysis Public

   Analysed 1,000 loan customers using Python, SQL and Power BI. Identified key default risk factors — High Risk segment shows 53.8% default rate vs 17.8% for Low Risk.

   Python

2. customer-segmentation-analysis customer-segmentation-analysis Public

   RFM customer segmentation of 4,338 retail customers using Python, SQL and Power BI. Champions generate 9x more revenue than Lost customers.

   Python

3. ecommerce-revenue-margin-analysis ecommerce-revenue-margin-analysis Public

   Analysed 100K+ e-commerce orders using SQL and Power BI. Identified revenue volatility drivers (RVI = 2.09) and margin constraints — contribution margin limited to 15.4% by shipping intensity.

4. online-retail-profitability-returns online-retail-profitability-returns Public

   Analysed 600K+ retail transactions across 38 markets using Python, SQL and Power BI. Identified Norway as a key profitability outlier with return impact exceeding 100% of net revenue.

   Python

5. user-lifecycle-churn-pipeline user-lifecycle-churn-pipeline Public

   End-to-end churn prediction pipeline: SQL cohort/RFM analysis, Python ML model (ROC-AUC 0.80), Power BI executive dashboard

   Python

6. airline-pricing-analysis airline-pricing-analysis Public

   Airline booking pace analysis and capacity-constrained pricing scenarios with Python and Power BI.

   Python