Quants worth following: Giuseppe Russo
It was not easy to leave Societe Generale, but I told myself that the expected value in building a startup is positive. If things work out, you'll make an impact in the industry. But even if things don't work out, it's a good life lesson, and I can always find another job.
"Quants worth following" is our latest interview series highlighting thought leaders in the quantitative trading industry actively sharing their knowledge and resources with the community.
In this edition, we connected with Giuseppe Russo , co-founder of EXVAi Research —a boutique firm specializing in AI-driven trading strategies for high-net-worth individuals, family offices, and sophisticated capital allocators. Before co-founding EXVAi, Giuseppe honed his data science and quantitative skills at Bending Spoons and on Societe Generale 's proprietary trading desk in Paris.
Giuseppe shares insights on his journey from statistics to quantitative trading, breaking into quant in Europe, his decision to leave Societe Generale to launch a startup, and offers valuable advice for aspiring quants.
"It was a long journey. I didn't study engineering, physics, math, or computer science. Instead, I pursued statistics because I was passionate about math as a kid. Statistics felt more pragmatic and connected to real-world problems, which led me to specialize in insurance."
After earning his bachelor's in statistics, Giuseppe pursued a master's in banking and finance, marking his shift into quant trading. His growing interest in AI and coding further drove this shift. He turned to online courses and academic research to bridge the gap in his skills.
Breaking into the quant field from Italy was another hurdle, as the industry there doesn't have the prominence it does in the UK, France, or the US. Giuseppe began his career at the tech startup Bending Spoons before securing a quantitative role at Societe Generale in Paris. It was at Societe Generale that he met two colleagues who would later become co-founders of EXVAi Research.
Giuseppe highlights the cultural differences across Europe, noting that France has a strong quant tradition. He explains:
“In Italy, the elite often send their children to schools focused on the humanities, which typically lead to careers in law. In contrast, France has a long-standing tradition of producing top-notch engineers, many of whom transition into the quant space. London and Paris are key hubs for quants, and many French-educated quants eventually move to London.”
"The main difference is that a startup's survival depends on software engineers and product managers, with code production being the primary revenue generator. In a startup, you might develop a mobile app, refine it, and then hire a data scientist to optimize revenue. In a prop shop, the quant or trader is the revenue generator, with the focus on high-quality research."
Giuseppe knew it was time for a bold change, so he took the leap and co-founded EXVAi Research with fellow investors Stefano Dalla Palma and Arnaud Bouchet. Despite their technical prowess and solid trading strategy, they quickly learned that startup success requires more than expertise.
Reflecting on the early days, Giuseppe shares, “We thought being good technically was enough, but the reality was far more challenging. We were faced with tasks beyond our expertise, like handling legal and tax matters, which were completely new to us. Every day had its surprises, but in the end, we managed to make it work.”
"It was not easy to leave Societe Generale, but I told myself that the expected value in building a startup is positive. If things work out, you'll make an impact in the industry. But even if things don't work out, it's a good life lesson, and I can always find another job."
As a recent founder, Giuseppe highlights two unique challenges encountered on his journey:
"In a large corporation, if you need tasks like data cleaning done, there's typically someone assigned to handle that. Your focus can remain on training your model because others are paid to ensure you have clean data. In a startup, however, you must handle everything yourself—from data preparation to legal, marketing, and even accounting tasks. For instance, I didn't know how to set up a company at first. It wasn't overly complicated, but I had to gather all the necessary information and figure it out on my own."
"There's a psychological and cultural aspect to consider. While San Francisco celebrates entrepreneurs as heroes pushing the economy forward, the response can be quite different elsewhere. In some countries, starting a business is viewed negatively. When I mentioned launching my startup, people often assumed I was struggling to find a job and offered to help me find one instead. It took time to adjust to these misunderstandings and rejections."
Giuseppe outlines his team's research approach, emphasizing how they apply data science principles to finance and trading.
"We approach research—and finance and trading in general—much like a data science problem. In data science, there's typically one target variable you're trying to predict. Similarly, we use data to create features and optimize models in finance.
Our process begins with raw data, usually financial data like prices, volumes, or fundamentals. From there, we perform feature engineering, generating hundreds of features that we hope will be informative. The simplest form of prediction is future returns or the direction of a stock’s price.
To increase the dimensionality of our feature space, we might create features like 5-day, 10-day, and 15-day moving averages. Then comes the next step, which is a big focus for us: using statistical techniques to select the most informative features. Instead of relying on conventional wisdom—such as using a 5-day moving average or a 3-month inflation expectation just because we've been told they work—we put everything into statistical models that provide answers probabilistically.
We're halfway through the process once we've selected the best features. The final step involves using machine learning models to take all these features and information to predict future outcomes."
Drawing from nearly a decade of industry experience, Giuseppe shares his top three pieces of advice for aspiring quants:
If the opportunity presents itself, consider attending a top institution to study engineering, physics, or mathematics. Beyond receiving a rigorous education, such an experience can open numerous doors and significantly enhance your career prospects.
This self-awareness will guide your career choices and help you align with your true interests and strengths. For example, if you excel in mathematics and have a theoretical approach, focusing on derivatives pricing might be a better fit due to its mathematical nature. Conversely, coin trading could be a better match if you're more pragmatic and inclined towards physics, as it is more statistically driven.
Posting interesting and relevant material on X can be a powerful way to get noticed by the big names in your field. Leverage it as a hiring tool during your search.
Check out the full interview on our YouTube here .