Trader Assistant (Working Student)

As a trader assistant, you’ll get a first-hand experience of what it’s like to work at IMC during your studies while adding value as an integral part of IMC’s trading team. It’s your chance to show us what you’re capable of, both analytically and as a teammate. You’ll be responsible for your own projects, with support from our skilled traders and engineers where needed. This is a unique opportunity to develop yourself professionally and to build that ‘can do’ mindset.

• →Support our trading teams by analysing data and building tools to make the trader’s life easier
• →Collaborate closely with IMC’s traders and engineers
• →Learn about the trading industry, what it is like to be trader and have the freedom to find your niche
• →Receive guidance from a dedicated mentor and the opportunity to build valuable connections with other full-time employees

• In your penultimate year of study in mathematics, physics, econometrics, or a related quantitative field at a university in the Netherlands graduating in 2026 or 2027
• Experience in Python is required
• Outstanding analytical skills
• A genuine interest in financial markets (no prior knowledge or experience is required)
• Available to work part-time (20-hours per week) in the IMC Amsterdam office for at least 6-months

Please note: If you have already applied for a Trading position during the current recruitment season and were not selected, you may reapply when the next recruitment season begins in Summer 2027. We encourage you to focus on enhancing your skillset before reapplying.

IMC is a research-driven trading firm where quantitative modeling, machine learning, and engineering shape how modern markets are traded. A stabilizing force in markets since 1989, we provide liquidity across trading venues, delivering the best outcome in value and risk management to investors. Using our own technology and capital, we build proprietary systems and algorithms that operate across global markets. Our researchers, traders, and engineers work as a collective, combining rapid experimentation, advanced infrastructure, and real-time feedback to turn insight into execution and execution into advantage.