Susquehanna is a premier options trading firm, but it is also a place that captures the spirit of academia, where researchers are free to pursue innovative ideas, learn new skills, and solve highly complex problems
Quantitative trading plays an ever-increasing role in the global financial markets. Automated algorithms analyse millions of financial instruments simultaneously, while mathematical models anticipate price movements on nanosecond timescales.
Susquehanna is a proprietary trading firm, meaning it invests its own capital in the markets. Susquehanna’s quantitative researchers – or “quants” – collaborate with traders and technologists to drive the company’s success. Quants design and implement the complex models and algorithms the firm needs to make rapid, well-informed pricing and trading decisions.
The quant advantage
Lyubo Panchev, a quant at Susquehanna with seven years at the firm, describes how quants collaborate across a wide range of instruments and problem types. “Our quants are all trying to mathematically understand the world and the financial markets,” he says, “and then we use that information to determine whether we want to make a trade or not.” While the challenges vary considerably across the firm’s different trading desks, that shared mathematical mission is what unites them.
The details of this work can differ from quant to quant, from devising new pricing approaches for financial instruments, to finding patterns in data to turn into trading signals, to developing specialized software to implement new trading strategies.
However, specialist knowledge in specific fields is not what Susquehanna is primarily interested in when hiring a new quant. Instead, the firm is looking for the types of transferrable skills that PhD students in STEM fields often possess. “We want to hire people who can reason through first principles and feel comfortable working in an uncertain environment with open-ended questions to which answers sometimes might not even exist,” says Panchev. “So that’s why we like to hire PhDs.”
A physicist, for instance, brings the skills and intuition for modelling systems with incomplete information – whether that’s modelling interactions in a complex system or inferring signal from noise in a vast dataset. The mental frameworks used by a theorist studying quantum field theory or an experimentalist analyzing data translate surprisingly well to pricing derivatives or spotting anomalies in market behavior.
Life outside academia
Panchev – a three-time International Mathematical Olympiad medallist with a PhD in pure mathematics from MIT – says that the most satisfying part of working at Susquehanna for him is that it preserves what he loved about academia, while at the same time addressing some of the shortcomings.
“The freedom to work on what you want is a unique advantage in academia, over pretty much any industry,” says Panchev. “But what quant researchers do at Susquehanna is close to that spirit.”
Though he enjoyed focusing on challenging questions surrounded by like-minded people, he found working on hyper-specialized academic problems during his PhD a slow, lonely slog. At Susquehanna, quants work on challenging problems, but never in isolation. Quantitative trading problems are invariably interconnected, requiring close collaboration between researchers, traders, technologists and many other experts, to connect all the pieces together.
What’s more, the environment is highly dynamic. “The impact is much more immediate, sometimes instantaneous,” he adds. “You can be looking at the data and then decide to make a change to your algorithm, tweak a few things, and five minutes later, you’re already getting data that’s from the change you just made – it’s a very fast feedback loop.”
When you add a highly desirable salary, benefits package, career development opportunities, and a company culture that values strategy games like poker to hone decision-making skills and apply them to complex financial markets, it is clear to see why a STEM PhD student might choose Susquehanna over a career in academia.
From toy problems to market mastery
To earn a seat at this table, applicants are put through their paces. The first and perhaps greatest challenge they face is getting through the interview process. Quant skills – like original thinking, intuition, and problem-solving – are not easily described in a CV or interview, they need to be demonstrated. But how can an applicant demonstrate those skills in an interview?
“We build interesting toy problems that are representative of what we do,” explains Panchev. “And then we give them time to think and work on it on their own, before reconvening to see how they approached the problem, and what they found out.”
The internship builds solid foundations in finance domain knowledge, machine learning, programming and data analysis
Successful applicants who are hired on immediately participate in a comprehensive 10-week internship – the first step in an intensive front-loaded education program at the company. This internship builds solid foundations in finance domain knowledge, machine learning, programming, data analysis, as well as what Susquehanna’s different quant groups do and how their work all fits together.
Panchev says that a typical direct full-time hire requires five months or more of very structured education, over time, however, the quant will be faced with more open-ended problems and need to chart their own way, free to explore their own ideas and methods.
“There’s a long, steep learning curve but at the end you become an expert,” he adds. “In a way, it’s very similar to how a PhD is structured.” This means that, while the barrier to entry is fairly high, the support system is robust, with a well-organized education program that ensures that everyone is equipped with the tools that they need to succeed.
For the successful STEM PhD student assessing their career options, Susquehanna offers a compelling proposition – the chance to remain a scientist, but on a stage where the stakes are higher, the collaborations deeper and more dynamic, and the results play out in real-time and have real-world impact.
