On my Telco Customer Churn Prediction project, I analyzed 7,043 customer records, prepared the data, and evaluated classification models. My weighted Logistic Regression model achieved an ROC-AUC of approximately 0.85, and I assessed thresholds to balance churn detection with customer outreach costs.
I’ve also used SQL to investigate retail sales performance and created interactive sales dashboards in Excel and Power BI. At Stayqurious, I supported learners as a Learning Coach, helping them work through technical and conceptual challenges.
