Role Overview:

The successful candidate will design, implement, and manage data-driven trading models across global macroeconomic assets. The position requires deep expertise in statistical and machine learning methodologies, alongside robust programming and data-handling capabilities. Applicants should bring a verifiable track record of high information ratio strategies deployed in real-market environments.

Key Responsibilities:

1. Develop and deploy systematic trading models across macro asset classes, primarily using futures and foreign exchange instruments.
2. Apply advanced quantitative methods—including time-series modeling, econometric analysis, and machine learning—to uncover alpha-generating signals.
3. Conduct extensive backtesting and stress testing to evaluate performance robustness, execution latency, and risk-adjusted return characteristics.
4. Collaborate within a research-driven environment to enhance alpha models, portfolio construction techniques, and signal processing infrastructure.
5. Monitor and evolve deployed strategies to maintain performance amid shifting market regimes.

Ideal Background:

1. Demonstrated experience in quantitative macro research or portfolio management, with a track record of alpha generation and strategy deployment.
2. Exposure to short- and medium-term systematic trading styles, ideally within timeframes of hours to two weeks.
3. Advanced academic training (PhD or MSc) in a quantitative discipline such as Financial Engineering, Applied Mathematics, Statistics, Computer Science, or Physics.
4. Strong coding proficiency in Python and/or C#, with working knowledge of SQL for data manipulation and extraction.
5. Eligible to work in the UK and able to operate effectively in a collaborative, research-intensive setting.