This is a technically deep, model-focused role, offering end-to-end ownership of the research and development cycle — from initial hypothesis and signal design through to production deployment and ongoing performance evaluation. You’ll be joining a team that prizes empirical rigor, strong coding ability, and original thinking grounded in statistical and mathematical foundations.
Role Overview
- Develop and refine systematic alpha models across asset classes (including Futures, FX, and Equities), leveraging high-quality, high-frequency datasets.
- Apply modern and classical statistical techniques to extract persistent predictive signals from noisy, non-stationary time series.
- Validate models using robust empirical and out-of-sample testing frameworks; challenge assumptions through critical analysis and performance attribution.
- Collaborate with senior researchers, infrastructure engineers, and execution specialists to bring strategies into production within a real-time environment.
- Actively contribute to research architecture, data tooling, and research methodology improvements.
Candidate Profile
- Advanced academic credentials (PhD or MSc) in a quantitative field such as Applied Mathematics, Physics, Statistics, Computer Science, or Engineering.
- Demonstrated depth in statistical modeling, time-series forecasting, and signal validation techniques.
- Strong Python programming skills, particularly in the context of numerical analysis, data processing, and research automation.
- Experience handling large, complex datasets and an appreciation for data quality, structure, and limitations.
- Independent problem-solving ability combined with a collaborative research mindset.
Desirable Additions
- Exposure to large-scale financial datasets and experience in systematic trading research.
- Familiarity with C++ or other compiled languages used for latency-sensitive components.
- Practical understanding of portfolio construction, execution modeling, or production deployment in a systematic setting.
This is an opportunity for a technically strong quant with a passion for research to contribute to a high-impact team working at the frontier of systematic trading. A deep curiosity, a scientific mindset, and a drive to build performant, real-world models are essential.
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