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Personal Background:
I architect, build, and ship production AI systems end to end — scoping the problem with stakeholders, designing the architecture, building and validating it, and owning it in production, often at 10M+-user scale across highly regulated industries. I have led this work since 2015 (data science since 2014), spanning Computer Vision, Natural Language Processing (NLP), and, most recently, Large Language Models (LLMs), multi-agent systems, and Generative AI. I am currently a Principal AI Engineer at FICO, delivering credit-scoring and analytics solutions for financial institutions, consumers, and businesses worldwide. Previously I was a Tech Lead at Vertex Inc, a global leader in tax technology, and a Senior ML Engineer at S&P 500 company LabCorp, building AI across drug diagnostics, drug development, and operations for leaders in the life sciences (see Labcorp SEC filings here). Earlier roles include enterprise Data Scientist at Bayer (a EURO STOXX 50 company), Quantitative Researcher (apprenticeship) at AQR (alternative quantitative strategies and factor-based trading), and Equity Trader at T3 Trading on Wall Street (licensed Series 56 by FINRA). Across these I have partnered directly with customers and executives — leading teams and delivering solo — turning ambiguous business problems into deployed platforms, mentoring the engineers who operate them, and owning the strategy, ROI, and P&L end to end. I think in reusable platforms rather than one-off projects, and I am equally at home in the boardroom and in the codebase. I also run a small algorithmic-trading fund (since 2011) and my own monetized YouTube Channel — feel free to connect on LinkedIn.
Though I began in finance, my AI career grew out of academia. I was a PhD student in Statistics at Columbia University from September 2020 to December 2021, hold a B.A. in Math and an M.S. in Finance from the University of Rochester, and an MBA from the University of Chicago Booth School of Business. My research centers on representation learning — Feature Learning, Deep Learning, Computer Vision (CV), and Natural Language Processing (NLP) — with earlier work in Financial Economics and Asset Pricing. I also teach graduate-level AI/ML and mentor students and early-career engineers, translating research into systems teams can own and run.
Architecture & Infrastructure Patterns:
Across a decade of building and shipping full-stack production systems — from whiteboard to POC to MVP to production, and on to scale at 10M+ users — I operate as a platform engineer at the director / senior-director level: architecting, building, and running cloud-native, event-driven AI infrastructure end to end, solo or as lead. I work from a matrix of the stack I apply across regulated industries — frontend through cloud-agnostic deployment — with security and scalability designed in from day one.
That full matrix is its own page: Architecture & Infrastructure Patterns — ten stack layers across logistics, healthcare, banking, education and fintech, with the two isolation problems that are genuinely hard (multi-tenant data isolation and credential isolation in agent tool-calling) written up in full.
Passion Project:
At leisure, I run W.Y.N. Associates, LLC, a registered legal entity in the state of New York, to pilot and drive for-profit personal passion projects.
- Clawdeck — an AI chatbot with its own cloud computer: chat with your files while it writes code, runs terminals, and builds documents for you.
- DeepSpeed Course — distributed training with DeepSpeed: multi-GPU examples and practical guides for neural nets and Hugging Face models.