What’s your background? What did you study?
I did a pure mathematics PhD before joining SIG. My thesis was on applications of probability theory to chaotic dynamical systems. While the subject matter of my PhD is not something that I regularly use at work, the research and abstract problem-solving skills that I developed during my PhD are indispensable tools that I still use every single day.
What sparked your interest in working for a trading firm over Academia?
Trading firms have no shortage of hard research problems to solve, which is not unlike academia. However, doing research at a trading firm is much more collaborative than in academia. While you may be the expert on a particular topic in the office, you will still be in constant discussion with other researchers, traders, and technologists about your work. In contrast, I found doing a PhD to be quite isolating – mathematics is so diverse that most mathematicians only have surface level familiarity with each other’s work. Also, in an academic career one has plenty of non-research responsibilities (e.g., teaching, administrative responsibilities). Quantitative researchers at trading firms are able to spend most of their time focussing on research. Lastly, research at a trading firm has a fast and tangible impact on the business compared to the very long peer-review process in academia.
Tell us about your experience in the Graduate Quant Research Program.
I was well supported during the onboarding experience. At the very beginning, I spent a few weeks doing a course on options theory, all while participating in social events with grads and attending weekly poker lessons. Over time, I was given increasingly difficult projects, and later I was invited to visit the headquarters in Philadelphia to attend an intensive course for quantitative researchers. There I met with many senior quants from our US business, attended lectures on SIG’s options trading stack, and worked through several mock studies from different business areas. Attending that course was the highlight of my first few years at SIG, and the connections I made there have served me well since returning to Sydney.
Tell us about a typical day for you.
There is never a typical day! At times I can be solely focused on a single longer-term project, while on other days I will be jumping between meetings and answering ad hoc research questions from traders or investigating the performance of improvements to our strategies. Having said that, I generally start the day by trying to talk to people in the Philadelphia office while our office hours overlap. I will then dive into whatever project is my current focus - this could involve building datasets in preparation for doing a study or creating a model, interrogating data to build signals to improve our production trading strategies, or checking that a new model has been implemented correctly before it is released into production. Often, I will have to talk to traders before the markets open to discuss ongoing projects. Meetings with other quants and teams can be scattered throughout the day.
Are there any specific skills or qualities that are essential to succeed in Research at SIG?
Aside from statistics and programming skills, I think good quants are thrifty, open-minded, and very curious, with a bit of a competitive streak. Our goal is to get to the truth of problems as cheaply as possible, and then to convert that truth into something tradeable – all the mentioned skills help in the pursuit of these goals.
How would you describe SIG’s growth, since you joined?
The firm has big ambitions for APAC markets, and consequently the Sydney office has been growing at a rapid pace. The atmosphere in the office is one of excitement and anticipation – nobody expects the work to be easy, but everybody is raring to do their bit.
What do you like best about working at SIG?
I enjoy the intensely collaborative and cross-disciplinary environment in which we do research at SIG – to get to the bottom of a particular question may involve talking to traders, operations, quants, or a variety of technologists to understand how each detail impacts the strategies that we are running. The work is also very challenging, which makes success all the more rewarding.
What projects and experiences have been most rewarding so far?
I’ve worked on a few projects that started as solo ventures building a model for a specific trading need that then evolved into collaborations with tech and trading in order to implement the model and incorporate it into our trading strategies. Seeing projects evolve from a simple concept to a fully-productionised component of a profitable strategy is incredibly rewarding, and it is a great feeling to have the support of your colleagues throughout the whole process.
What three pieces of advice would you give to a graduate interviewing at SIG?