Bridging the gap between theoretical modeling and robust production deployment. Specialized in Financial AI, LLM Strategy, and Mission-Critical Infrastructure.
Core Technologies
I am a Senior Data Scientist and Systems Architect with over 8 years of specialized AI/ML experience, supported by a 25-year foundation in mission-critical infrastructure.
My career has been defined by a unique ability to bridge two worlds: the theoretical complexity of machine learning models and the rigorous demands of production engineering. I don't just build models; I architect scalable solutions that solve complex business challenges in Financial AI and predictive analytics.
Spearheaded machine learning solutions (Linear Regression, SVM, Random Forests) to optimize global technology infrastructure.
Engineered a predictive maintenance ML model (LSTM, ARIMA) to forecast chemical spills, projecting annual savings of ~$1M.
Founded and led a professional services firm. Managed an 11-engineer team and implemented virtualization and cloud infrastructure for over 25 enterprise clients.
Sun Microsystems, Banco Santander. Managed mission-critical Unix environments and implemented High Availability Clusters.
Machine learning for anxiety and depression profiling and risk assessment in the aftermath of an emergency
Artificial Intelligence in Medicine (Volume 157)Published Patent
Point-in-Time Relative Outlier Detection
Issued Patent
Generating Enhanced Queries Using ML Models
Filed Patent
Generating Vector-Based Recommendations
Published Patent
Cross-Cluster Transaction Risk Assessment
See my full list of proficiencies, certifications, and early-career accomplishments in the PDF.
View Technical ResumeA scalable ML pipeline for detecting anomalies in high-volume corporate transactions using Isolation Forests.
LLM-based Q&A system for enterprise documentation. Implements RAG with vector database retrieval.
I am available for consulting and architectural reviews. Whether it's bridging the gap between POC and Production or optimizing high-load pipelines, let's talk.