Unified fraud detection and churn prediction platform with advanced ML pipelines, feature engineering, behavioral analytics, and production-ready inference.

End-to-end telco customer churn analysis data analyst project: raw Kaggle dataset ingestion, MySQL data warehousing, Python-based cleaning/modeling, and Power BI dashboard. Project includes actionable business insights, model-driven recommendations, and revenue impact.

Built a churn prediction model to retain subscription customers. Expertly preprocessed data, engineered features, and optimized models for accuracy. Deployed the model via Flask for real-time predictions, showcasing end-to-end data science skills.

Predicting telecom customer churn using machine learning models, EDA, and business-driven insights.