Responsibilities
- Research and implement high-frequency trading strategies, leveraging deep knowledge of market microstructure
- Analyze large-scale market data to uncover inefficiencies and design robust, data-driven models
- Build and maintain simulation and backtesting tools aligned with real-world trading conditions
- Write and optimize production-grade code for signal generation, execution logic, and infrastructureponents
- Collaborate across disciplines to ensure seamless integration of research and engineering efforts
- Monitor strategy performance, adapt models to changing market conditions, and manage risk
Requirements
Strong experience in high-frequency trading or systematic strategies within crypto or traditional marketsAdvanced programming skills in Python , along with proficiency in at least onepiled language ( Rust preferred , C++ or Go also wee)Deep understanding of market microstructure and the technical nuances of low-latency tradingBackground in a quantitative discipline such as mathematics, statistics, physics,puter science, or engineering (MSc or PhD preferred)Practical experience working with large datasets, real-time data pipelines, and cloud-based research environmentsFamiliarity with version control systems (Git), Linux / Unix environments, and containerization tools such as DockerStrong problem-solving ability, high attention to detail, and a mindset geared toward continuous improvementLocation
This role is based in London . We believe in the power of close collaboration, and candidates should either be located in London or willing to relocate. Support for relocation is available.
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