Yiqiao Yin — Data Science, AI, and Markets

Home

Personal Background:

I architect production AI systems for financial institutions and other highly regulated enterprises. The pattern I have seen across a decade in this space: the demo takes a week, the deployment takes a quarter, and the gap is never model capability. It is evals, guardrails, audit trails, and a governance story that risk and compliance teams can sign their names to. That gap is where I work.

I am an Advanced AI Architect Manager at Accenture, designing agentic AI and LLM architectures that take enterprises from promising pilot to governed production. I am equally at home whiteboarding with engineering teams and sitting across from CIOs, CAIOs, and model risk leaders, because I have spent my career on both sides of that table — and I build teams that can hold the architecture after I leave the room.

My background is finance-native. At FICO I was a Principal AI Engineer and founding member of the GenAI Engineering team, leading engineers who built production Claude and MCP-based agentic systems serving Tier-1 banks under multi-cloud, multi-tenant compliance constraints. Before that: Tech Lead at Vertex Inc, a global leader in tax technology; Senior ML Engineer at S&P 500 company LabCorp, building AI across drug diagnostics, drug development and operations (see Labcorp SEC filings here); enterprise Data Scientist at Bayer, a EURO STOXX 50 company; Quantitative Researcher (apprenticeship) at AQR, on alternative quantitative strategies and factor-based trading; and Equity Trader at T3 Trading on Wall Street, formerly Series 56 licensed by FINRA. I speak model risk and system design as native languages. I have been in AI/ML since 2015 and data science since 2014, across Computer Vision, Natural Language Processing (NLP) and most recently Large Language Models (LLMs), multi-agent systems and Generative AI — often at 10M+-user scale.

I also teach as a Clinical Assistant Professor at Pace University and build production software end to end as a solo developer, which keeps my architecture opinions honest. I run a small algorithmic-trading fund (since 2011) and a 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.

DuoLang — when your parents move in and don't share a language with your spouse, the hard part isn't grammar, it's getting through Tuesday. A phrasebook built room by room: tap the kitchen, tap Can you, tap warm her milk, and you get the sentence in English and Chinese with pinyin and audio for both. When something comes up that isn't in there, one tap records, one tap stops, and a couple of seconds later you're both looking at the same sentence in both languages.
Clawdeck — an AI chatbot with its own cloud computer: chat with your files while it writes code, runs terminals, and builds documents for you. Decommissioned and taken offline. Contact me on LinkedIn if interested.
DeepSpeed Course — distributed training with DeepSpeed: multi-GPU examples and practical guides for neural nets and Hugging Face models.
Project Acuity — point your phone at something and it tells you what you're looking at. Live road commentary while you drive, and a colour reader that names garment colours out loud, built for red-green colour blindness. Passcode on request.