🧮 The Python Quants
Founder & CEO delivering quantitative finance training and tooling for modern quants.
Visit TPQ ↗
About
Quant technologist integrating finance, AI, and automation.
I blend academic rigor with production-grade execution to empower finance professionals transitioning into an AI-first era.
With a Ph.D. in Mathematical Finance, I lead The Python Quants and The AI Machine, focusing on algorithmic trading, Python-driven analytics, and enterprise AI adoption. My work bridges research and industry impact through books, programs, and advisor roles.
Today, I partner with institutions and practitioners to build AI-native workflows: from LLM-assisted research pipelines to quantitative trading systems. My teams deliver portfolio-ready education, code assets, and community programs that help quants stay ahead.
Initiatives & Roles
Hands-on programs, products, and communities for AI and finance innovators.
Explore the ecosystem powering Python, quantitative finance, and generative AI adoption worldwide.
🧠 The AI Engineer
Flagship training program for AI-native builders. Ship production LLM systems with hands-on capstones.
Join TAE ↗🎓 CPF Program
Director of the Certificate in Python for Finance — 400+ hours of code, video, and projects.
Learn about CPF ↗🤖 The AI Machine
Building applied AI systems and education that push automation across the capital stack.
Discover AIM ↗📚 Publications
Author of ten books on Python, quantitative finance, and applied machine learning for markets.
View catalog ↗▶️ Content & Media
Creating instructional video series and AI-powered podcasts for the quant community.
Watch on YouTube ↗🏛 Academic Partner
Lecturer at CQF and EPAT programs, bringing advanced Python and AI workflows to practitioners.
CQF insights ↗🌐 Quant Communities
Organizing meetups in London, New York, and beyond to grow the Python for finance network.
Join meetups ↗💡 quants@dev
Leading developer community initiatives that align quant engineering with AI-native practices.
Explore community ↗📦 DX Analytics
Author of the DX Analytics Python package for valuation, risk analytics, and derivatives pricing.
Access GitHub ↗
AI-Powered Discussion Papers
Exploring expertise, automation, and quant research in the age of AI.
Rapidly developed with GenAI tooling, these papers capture key theses and frameworks driving our programs.
The Rise of the AI Engineer
AI engineers emerge as the alchemists of GenAI — blending data, models, and governance to unlock institutional advantage. Explore case studies and see how The AI Engineer program builds this capability.
Why Coding Skills Still Matter in the Age of AI
Programming remains the engine of quantitative finance. This paper highlights how GenAI amplifies — not replaces — rigorous coding practices in research and production.
The Maestro and the Apprentice: Expertise in the Age of AI
An exploration of human-AI collaboration for quants. Learn how domain mastery and AI copilots combine to accelerate innovation.
GenAI in Quantitative Higher Education
Strategies for integrating generative AI into curricula, enabling faster build-measure-learn cycles for finance programs.
Two Tales of Automated Quant Research
A comparative narrative on automation-first vs. human-centered quant workflows — and how the future blends both.