I help C-suite leaders build the latter — translating AI complexity into business clarity, and designing products that generate real returns across their full lifecycle.
About
I've led data science and AI product across industries and company stages — most recently at Meta, and as Sr Director of AI Product at Charles Schwab — and built the Executive Programs division at Metis that taught C-suite leaders how to think about machine learning before it became a board-level conversation.
I advise, write, and speak for the leaders navigating those same questions now. My perspective is practical, my assessments are honest, and I have no interest in theater.
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Most AI investments fail quietly — not from bad models, but from misaligned strategy and undefined ROI. I help leadership teams ask the right questions, set the right goals, and build the accountability structures that turn AI initiatives into measurable business outcomes.
Learn moreI design AI products with the full lifecycle in mind: not just what works technically, but what generates revenue, scales cost-effectively, and evolves as the business grows. From initial roadmap to production, I keep the business model in the room.
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A multi-agent system that takes a topic and learning objectives and produces research summaries, class notes, presentation outlines, and PowerPoint drafts — with an autorater that evaluates its own output.
Read essay →A talk on the real-world application of generative AI in industry — what's working, what's hype, and where the field is actually headed. Delivered at ODSC West's Gen Ai X Summit, 2024.
Read essay →The full dissertation submitted to Cornell University's Field of Statistics, 2023. A rigorous treatment of data quality applied to America's COVID-19 data — the problems, the metrics, and a framework for thinking about fitness for use.
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