I combine mathematical and technical depth with practical business execution. I understand capital markets, finance, data, AI, and systems — and I care about applying compute, automation, and technical thinking to real-world problems where demand is high and resources need to be used well.
I build repeatable processes and well-organized systems. Whether it's proposing an automated compliance workflow, designing data extraction tools, or helping coordinate logistics for a 400-person event, I work from first principles. I am highly comfortable with the engineering workflows that keep production systems running, and I always ensure my technical execution aligns with the broader business strategy.
I stay close to where technology is going—especially AI, agentic workflows, and automation—while staying grounded in what delivers real business value. As President of McGill CodeJam, I helped integrate enterprise AI standards into student technical challenges. At CI GAM, I gained direct exposure to how capital markets are shifting. I adopt new tools quickly, but I also know when simpler, more robust approaches win.
My Math and Computer Science degree at McGill gave me a rigorous foundation in algorithm design, statistical reasoning, and computational theory. I apply that rigor to machine learning pipelines, data-intensive systems, and financial analysis. I think carefully about time complexity, data architecture, and the tradeoffs behind every technical decision.