Quantitative Researcher - HFT Commodity Futures

IMC is looking for experienced quant researchers to develop high frequency delta one trading strategies and predictive models for the China Commodity Futures & Options market. If you’re excited about helping to push the boundaries of what we can do with Machine Learning in trading, unlocking the significant edges we have in execution, and collaborating to become the best trading firm worldwide, this may be the role for you.

You will be responsible for performing large scale data analysis to derive statistically profitable predictions of market behaviour. These predictions are used to inform all of our trading, and improvements have a high and visible impact across the office. You will also help to shape the direction we take across research and tooling. We have longstanding and significant edges across market access, global reach, Options understanding and low latency. The rapid growth we’ve already seen in Machine Learning has unlocked these edges, and some of the most interesting and impactful problems are now being tackled.

You will work as part of an established and growing research team, collaborating closely with traders, software and hardware developers to find improvements to our models and see them impact our production results. IMC competes and wins as a team, with open idea sharing and collaboration across disciplines, desks and offices.

Your Core Responsibilities:

• Combine creativity and experience to rapidly generate high quality, testable alpha signals
• Refine and leverage deep understanding of market microstructure and order book dynamics in China & global Commodity Futures, to create powerful features
• Apply statistical and machine learning techniques with strong discipline around robustness and overfitting
• Collaborate closely with trading and engineering teams to translate research into production strategies

Your Skills and Experience:

• 3+ years of experience in high-frequency alpha research for China Commodity Futures, with strong track record
• Strong foundation in probability and statistics, and significant practical experience with at least one mainstream ML approach
• Experience working with large, high-frequency trading datasets
• Excellent programming skills in at least one language (Python preferred)
• Practical mindset with a focus on deployable, real-world edge