🧮 The Python Quants
Founder & CEO delivering quantitative finance training and tooling for modern quants.
Visit TPQ ↗Educating the next generation of AI engineers with The AI Engineer program.
Founder of The Python Quants and The AI Machine. Author, educator, and builder empowering finance professionals and software engineers to accelerate quantitative finance with Python, AI, and automated research workflows.
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.
Explore the ecosystem powering Python, quantitative finance, and generative AI adoption worldwide.
Founder & CEO delivering quantitative finance training and tooling for modern quants.
Visit TPQ ↗Flagship training program for AI-native builders. Ship production LLM systems with hands-on capstones.
Join TAE ↗Director of the Certificate in Python for Finance — 400+ hours of code, video, and projects.
Learn about CPF ↗Building applied AI systems and education that push automation across the capital stack.
Discover AIM ↗Author of ten books on Python, quantitative finance, and applied machine learning for markets.
View catalog ↗Creating instructional video series and AI-powered podcasts for the quant community.
Watch on YouTube ↗Lecturer at CQF and EPAT programs, bringing advanced Python and AI workflows to practitioners.
CQF insights ↗Organizing meetups in London, New York, and beyond to grow the Python for finance network.
Join meetups ↗Leading developer community initiatives that align quant engineering with AI-native practices.
Explore community ↗Author of the DX Analytics Python package for valuation, risk analytics, and derivatives pricing.
Access GitHub ↗Rapidly developed with GenAI tooling, these papers capture key theses and frameworks driving our programs.
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.
Programming remains the engine of quantitative finance. This paper highlights how GenAI amplifies — not replaces — rigorous coding practices in research and production.
An exploration of human-AI collaboration for quants. Learn how domain mastery and AI copilots combine to accelerate innovation.
Strategies for integrating generative AI into curricula, enabling faster build-measure-learn cycles for finance programs.
A comparative narrative on automation-first vs. human-centered quant workflows — and how the future blends both.