Real-world solutions in data engineering, machine learning, automation, and enterprise systems built during my professional experience.
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High-performance XML processing system with custom streaming algorithms for multi-gigabyte financial documents. Achieved 75% faster processing and 60% memory reduction through constant memory usage patterns while maintaining 99.9% data accuracy with comprehensive validation.
Comprehensive ETL ecosystem integrating multiple ERP systems including banking platforms, insurance policy systems, and external vendor feeds. Achieved 99.5% pipeline success rate, 80% reduction in manual processing, and 70% improvement in processing efficiency through intelligent scheduling and automated optimization.
Enterprise Python system integrating Moody's Orbis API for automated corporate ownership analysis using Italian P.IVA search. Features NetworkX graph-based calculations, Ultimate Beneficial Owner detection, circular ownership handling, and path tracing algorithms for regulatory compliance.
Mathematical optimization system using Gaussian distance scoring, social clustering, and Lucy penalty weighting for intelligent office seating assignments. Implements atomic database operations preventing race conditions with zero seat conflicts and 89% user satisfaction.
End-to-end ML system for predicting loan defaults using ensemble methods (XGBoost, Random Forest) with time-based cross-validation. Achieved 85%+ precision, 78%+ recall, and 0.89 ROC-AUC through advanced feature engineering and hyperparameter optimization with Optuna.
Autonomous rescue robot for hazardous maze navigation using advanced pathfinding algorithms, computer vision, and multi-sensor fusion. Winner of Best Software Award at RoboCup Junior 2017 Nagoya, Japan with 95% victim detection rate and 8-minute maze completion time.
I'm always open to discussing new opportunities in data engineering, machine learning, and enterprise solutions. Feel free to reach out using the contact links below!