Built by Practitioners, For Practitioners
Our team brings decades of real-world experience from top financial institutions, research labs, and technology companies to create education that actually prepares you for the industry.
Meet Our Core Team
Each member brings unique expertise from different corners of quantitative finance and machine learning, creating a comprehensive learning experience grounded in real practice.
Zara Khwaja
Head of Quantitative Research
After completing her PhD in Mathematical Finance at Cambridge, Zara spent eight years developing algorithmic trading strategies at a London-based hedge fund. She noticed a gap between academic theory and practical implementation that motivated her to join our educational mission. Her approach focuses on teaching the messy realities of financial modeling that textbooks often skip.
Marcus Webb
Senior Machine Learning Engineer
Marcus transitioned from Goldman Sachs' quantitative research division to focus on education after realizing how many bright graduates struggled to bridge the gap between university ML courses and financial applications. He specializes in making complex algorithms accessible while maintaining their mathematical rigor. His weekend hobby involves building neural networks to predict his local cricket team's performance.
What Drives Our Teaching Philosophy
We believe the best way to learn quantitative finance is by working with real data, real problems, and real constraints. That's why our approach emphasizes practical application over theoretical perfection.
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Experience Over Theory
Every concept is taught through actual market scenarios and case studies from our professional backgrounds.
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Tools That Matter
We focus on the programming languages, libraries, and platforms you'll actually use in professional settings.
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Honest About Limitations
Financial markets are unpredictable. We teach both what works and what doesn't, preparing you for reality.