Engineered end-to-end machine learning pipeline integrating preprocessing, model persistence, and real-time inference scoring across 15+ variables. Implemented API-based scoring framework validating outputs and monitoring model stability improving prediction consistency by 10% across deployed analytics workflows.

Developed anomaly detection models by engineering behavioral features and calibrating classification thresholds to evaluate 12+ risk indicators. Validated predictive performance using cross-validation and precision-recall metrics while building dashboards tracking security insights achieving 99.8% consistency across analyzed web traffic datasets.

Designed executive dashboards comparing actual versus budget outcomes analyzing 18+ KPIs across product lines and regions. Optimized data models and calculated measures enhancing variance interpretation improving reporting accuracy by 30% supporting strategic business decision-making processes.