At IMC, traders, engineers and quant researchers work closely together to develop and execute cutting-edge trading strategies. The latter, perhaps lesser-known position often sparks the most curiosity. We spoke to Liam about what it's like to work as a quant researcher and how he's making a tangible impact on IMC’s trading strategies.

What led you to IMC and the quant researcher position?

You could say that the choices I made as a student and early in my career led me here. I studied maths and computer science at university. After graduating, I worked as a trader for another firm, where my focus was very much on the operational side of trading.

The quant researcher role uses a raft of machine learning techniques to leverage very high amounts of data to show strong predictive power. This includes classical machine learning, deep learning and large language models. There's a strong focus on using data science and statistics, as well as open-ended research. That last part really appealed to me: I liked the idea of using my skills and creativity to solve new problems that will help improve our trading models and drive success.

One of the reasons I applied to IMC was the focus the company has on technology. Our developers are involved as part of the overall trading strategy, and the company invests heavily in ensuring we fully leverage new technological advances that can improve the business. As someone with a long-standing interest in machine learning, this was music to my ears!

Can you explain what an IMC quant researcher does?

In the simplest of terms, our job is to find ways to improve IMC’s trading models and algorithms. This can mean anything from updating a model’s features or modifying its objective, to completely changing the modelling approach.

We come up with ideas to improve our models by undertaking research projects. We then statistically back-test our ideas using historical trading data to see how the model would perform in a specific trading scenario or market situation. Our work often takes the form of experiments – for example, we make small incremental changes to a model to see how its performance changes relative to the baseline. We run the updated model through a series of tests before deciding whether to accept the change and then send the updated model to production.

Where does machine learning come into it?

Machine learning removes many of the manual aspects of research, allowing you to analyse large data and statistical sets at considerable speeds. As a quant researcher, this means you can work with more data, run more experiments and explore a wider range of possibilities than ever before.

But our work is also very people-driven, and most projects hinge on effective collaboration. Quant researchers sit alongside IMC’s traders and quant traders who focus on the operational side of trading or developing our trading strategy. We also work closely with developers to put models into production and regularly exchange knowledge and ideas with researchers on other trading desks.

As you can see, it's a multi-faceted role – and that's where my experience in both trading and technology comes in handy.

What does a typical day look like for you?

When I arrive at the office, I grab a coffee and some breakfast. Then I’ll spend the first part of the morning checking the results of the experiments that we had running overnight and discussing them with my team.

From this point, my day can go in several different directions depending on my team’s priorities. This could includes training new model architectures and evaluating them against existing benchmarks. I could be implementing new ideas from recently published academic research. Or my day might see me conducting feature engineering studies, often collaborating directly with traders to transform their insights into rigorous statistical analyses and optimised model inputs.

We also spend a lot of time connecting as a team. I recently took on the responsibility of managing a recent graduate, so I also invest time every day in coaching them and helping to guide their career development. Likewise, I have regular check-ins with my own manager to make sure I'm meeting my targets and moving in the right direction strategically.

What do you most enjoy about the role?

Working in quant research is very exciting. With advances in machine learning, the world of trading research has changed so much in recent years. Things are still evolving, and I love having the opportunity to develop new skills and insights and be part of bringing the most advanced, cutting-edge developments to IMC.

IMC is a place where you can really make a difference. Everything moves so fast that it's all hands-on deck to drive the business forward and achieve our goals. Within Trading, we have regular meetings to make sure everyone knows what the priorities are and that we're all pulling in the same direction.

What this all means is that everyone has the opportunity to make a real difference – people will listen to your ideas, even if you've only recently joined the company, and you'll always be asked for your opinion.

What do you think makes an ideal Quant Researcher?

You need a rock-solid grounding in maths and statistics – that goes without saying – but you also need to be a good communicator. Quant research at IMC is a very collaborative role, and it's important that you can work with a wide range of people, helping to coordinate projects across teams and desks, and communicating your progress to people across the business.

What we rely on is a constant desire to learn and improve yourself. As a researcher, you have a lot of autonomy in deciding where to focus your efforts or what steps to take on a particular project. So, you need to be a self-starter - someone who's willing to take the initiative and come up with ideas on how to move things forward.

For anyone interested in quant research, I'd encourage you to think outside the box and find ways to develop your knowledge of relevant topics. If you’re still studying, you could try entering a data science competition or getting involved in research projects that apply machine learning outside of the typical university context. By being proactive, you can prepare yourself for the kind of work we do as quant researchers, particularly at IMC.

Register for our upcoming livestreamed and in-person quant research masterclass, where we demystify quantitative research. Register here.

Do you have what it takes to join IMC’s Trading team as a quant researcher?

Check out our latest vacancies here.