● Designed and deployed production-grade regression models using Scikit-learn, reducing wafer measurement time by 30%, accelerating manufacturing feedback loops. ● Developed classification pipelines leveraging XGBoost and Random Forest classifier to detect wafer defects, improving early fault detection by 15% and minimizing downstream waste. ● Built internal Streamlit dashboards to monitor real-time wafer health, accelerating engineering diagnostics by 2 weeks. ● Created scalable ETL workflows and deployed pipelines via BigQuery, achieving 40% faster analytics across unstructured FAB sensor data. ● Implemented root cause analysis combining statistical modeling, feature engineering, and causal inference, resulting in $10M annualized yield recovery. ● Collaborated with manufacturing stakeholders to integrate ML-driven insights into core production systems, boosting operational throughput by 20%.

● Created churn prediction models using Logistic Regression, enabling targeted retention efforts that increased user retention in the Indian Market by 5%. ● Delivered real-time analytical insights via interactive KPI-based Tableau dashboards, guiding A/B testing decisions for improved user engagement. ● Automated error reporting pipelines using Google Play API and Python, reducing manual QA cycles by 30% through enhanced error triaging.