Mattia Spreafico is a quant based in Switzerland with an MSc in Quant Finance and a background in Mathematical Engineering from Politecnico di Milano.

In this episode, we go beyond job titles and get into what the next generation of quants is actually dealing with day to day inside large institutions, where speed, correctness, and deployment constraints collide.

We talk about how AI is already changing the quant workflow in practice, not as hype but as a default tool for research, coding, and iteration. Mattia shares a grounded view on where LLMs genuinely help, where they still fall short in finance, and why data quality and access are still the real foundation. We also dig into the uncomfortable tradeoff nobody wants to admit: a perfect review slows you down, but moving fast increases risk, so the game becomes building better monitoring, better controls, and faster reaction when something breaks.

If you care about how quant research is evolving from idea to production, why deployment can be harder than modeling, and what skills will matter most when everyone can “code” but fewer can design robust systems, this conversation will hit.

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