During February 2026, Ruxu developed end-to-end machine learning workflows for customer churn analytics within the microsoft/fabric-toolbox and microsoft/fabric-samples repositories. Leveraging Python, Power BI, and Azure, Ruxu engineered data ingestion, feature engineering, model training, and batch scoring pipelines that integrated predictive insights directly into BI reports. The work enabled real-time churn prediction by embedding ML models into Power BI’s semantic layer, enhancing business intelligence capabilities. Additionally, Ruxu improved documentation quality by resolving image rendering issues in Markdown files. The depth of these contributions reflects a strong grasp of data engineering, machine learning, and documentation best practices within enterprise analytics environments.