Quantitative Risk Manager

• →Monitor and measure the market risk exposure of our trading activities, partnering closely with trading desks to recommend strategy adjustments and risk mitigation ahead of adverse events
• →Build independent backtesting models to challenge trading strategies, evaluating performance with risk-adjusted metrics such as Sharpe, Sortino and Calmar ratios
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  Track market developments and the macro calendar, and run stress tests and scenario analyses to assess potential impacts on the trading book
• →Utilize Python-based tools and libraries for stress testing, and scenario analysis as well as generally designing and contributing to local risk management tooling
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  Work with global risk, trading, software development and data engineering teams to design and deploy risk controls within IMC’s proprietary global risk management and trading systems
• →Drive the operational incident management process with key stakeholders to structurally improve infrastructure, processes and governance
• →Ensure adherence to regulatory requirements and internal risk policies
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  Train and support traders on risk tools, methodologies and best practices

• →3+ years of relevant experience in capital markets, e.g. at a trading firm, bank or asset manager
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  Bachelor's or master's degree in a quantitative field, with strong academic performance
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  FRM/ CFA/ CQF preferred but not required
• →Proficiency in Python, with demonstrated experience in data analysis, scripting, and dashboard or tool development
• →Strong understanding of options theory, including Greeks, volatility, and pricing dynamics
• →Excellent verbal and written communication skills, with the confidence to challenge traders constructively
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  A proactive problem-solver who thrives in a fast-paced, high-pressure environment
• →Experience analysing and managing risk across a portfolio of equities, futures, and options
• →Familiarity with stress testing methodologies and risk management frameworks

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.