Senior Fraud Strategist
Current• Managed end-to-end product ownership for in-line and offline decisioning across the account space, efficiently handling over 7 million transactions daily, enhancing fraud detection capabilities and operational efficiency.• Developed a strategic framework for hybrid machine learning that combined advanced neural networks and probabilistic modeling, focusing on real-time transaction monitoring; this involved enhancing the model stack, applying ensemble techniques and Bayesian optimization for feature selection, which collectively boosted decision accuracy by 1.3% across approximately 2.7 billion transactions annually.• Managed external engagements with industry vendors and collaborated with cross-functional stakeholders including Product Managers, Engineering Managers, Engineers, and Business Analysts within the internal engineering organizations focusing on current services and developing proofs of concept for future initiatives, employing Agile / Scrum, Kanban, and Lean principles to enhance project fluidity and ensure rapid prototyping.