Murad Aladdinzade

Developed XGBoost churn model reducing monthly subscriber churn by 1.5%; clustered customers into seven cohorts via K-means for targeted campaigns.

Developed XGBoost churn model that reduced monthly telco subscriber churn by 1.5%, strengthening retention strategies. Clustered customers with K-means into seven cohorts (2 high-value, 3 mid-tier, 2 low-value), enabling targeted campaigns.

Shaped AI capabilities with OpenCV-based computer vision model in AWS SageMaker Notebooks; deployed FastAPI-based AWS Lambda endpoints for real-time model inference; automated UI-element and cursor-location detection using OpenCV.