About
At JGW, I am leading our transformation into a truly data-driven organization, where AI + analytics is not a support function, it is the operating system for the entire business.
I have built and scaled analytics organizations across travel (Priceline), publishing (Barnes & Noble), financial data (S&P Global), and consumer financial services, proving that when technical excellence meets business acumen, data becomes a core asset that improves ROI.
Fluent in business and technology (Harvard MBA + Computer Science), I believe the future belongs to leaders who can bridge both worlds.
Impact Areas
- Scaled analytics from zero to enterprise scale across five industries
- Built teams that shape outcomes, not only report metrics
- Architected data products that became core revenue drivers
Experience
Chief Digital & AI Officer · JG Wentworth
Mar 2022 - Present · New York City Metropolitan Area
SVP Analytics & Data Science · JG Wentworth
Apr 2021 - Mar 2022 · New York City Metropolitan Area
Vice President of Analytics · Priceline
Jan 2019 - Mar 2021 · New York City Metropolitan Area
Head, Data and Analytics Products · Barnes & Noble Education
Dec 2016 - Dec 2018 · New York City Metropolitan Area
Vice President, Data Products · S&P Global
Jan 2011 - Sep 2016 · New York City Metropolitan Area
Director, Data Products · McGraw Hill
Aug 2007 - Jan 2011 · New York City Metropolitan Area
Books
AI Filmmaking Using Google's Veo
Dec 31, 2025
A hands-on guide to producing professional AI-assisted films with Google Veo, from prompt design to final cinematic export.
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The AI Takeover: from Hollywood to Wall Street and How to Future-Proof Your Career
Dec 25, 2025
An accessible overview of AI's cross-industry disruption with practical frameworks for staying career-relevant in an automated economy.
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Code the Odds: Prediction Market Trading Using Python
Dec 26, 2025
A practical build-from-scratch playbook for creating Python bots that price probabilities, detect arbitrage, and automate prediction-market trades.
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Scale AI
Dec 25, 2025
A production-focused guide to scaling ML on GKE and Terraform, covering distributed training, serving, autoscaling, and cloud cost control.
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AI Inference with Ollama, llama.cpp, and vLLM
Jan 4, 2026
A step-by-step handbook for running and optimizing open-source LLM inference from local hardware to high-throughput production clusters.
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DuckDB for AI: Accelerating Machine Learning Workflows
Dec 27, 2025
Shows how to use DuckDB's columnar engine to speed feature engineering, analytics, and end-to-end ML pipelines without cluster overhead.
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Patents
- US 8156340: System and method for securing system content by automated device authentication II (2012)
- US 7480803: System and method for securing system content by automated device authentication I (2009)
Contact
For speaking, advisory, or collaboration inquiries, message me directly on LinkedIn.
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