As a Graduate Quantitative Researcher, you will work with experienced researchers and developers in a fast-paced, data-driven environment. You will learn how trading ideas are researched, tested, and deployed, while contributing to live strategy development from early in your career.
Your Core Responsibilities:
- Research and test data-driven trading ideas
- Analyse large and complex datasets from cryptocurrency exchanges, DeFi protocols, and financial markets
- Build, test, and improve models, signals, and algorithms that support trading strategies
- Work with IMC's cutting-edge data, software, and high-performance computing infrastructure
- Collaborate closely with researchers, developers, and engineers to turn research into production-ready strategies
- Learn how to evaluate trading opportunities with a focus on performance, scalability, robustness, and risk
Your Skills and Experience:
- Final-year student or recent graduate in Mathematics, Statistics, Physics, Computer Science, Engineering or a related quantitative field
- Strong analytical and problem-solving skills, with the ability to learn quickly
- Programming experience, ideally in Python. Familiarity with C++ is a plus
- A genuine interest in financial markets, trading, crypto, or DeFi
- Comfortable working with data and applying quantitative methods to real-world problems
- Curious, collaborative, and eager to take ownership in a fast-moving environment
Prior experience in trading, crypto, or financial markets is helpful but not required.
This is an on-site role based in Zug, Switzerland, with very limited flexibility for working from home.
About Us
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.
