This is a permanent position.
This position sits at the intersection of quant engineering, data infrastructure, and research tooling, where you'll design models, build reusable analytics libraries, optimize large-scale market data pipelines, and turn investment ideas into production-ready Python components.
What you'll do:
- Develop, test, and refine predictive trading signals using statistical and quantitative methods
- Analyse large, complex datasets to uncover patterns, behaviours, and alpha opportunities
- Build research tools, data pipelines, and code libraries to support fast experimentation
- Run backtests, model validations, and scenario analyses to evaluate ideas
- Collaborate closely with traders and engineers to improve model robustness, execution logic, and overall strategy efficiency
- Assist in monitoring strategy performance and identifying areas for optimisation
What we're looking for:
- Prior experience in systematic, algorithmic, or high-frequency trading
- Strong programming ability (Python and/or C++ preferred), with clean, efficient coding habits
- Solid grounding in statistics, probability, linear algebra, and quantitative modelling
- Experience working with large datasets and building analytical workflows
- Hands-on exposure to model development, testing, and iteration
- Curiosity-driven mindset with the ability to break down problems and run structured experiments
- Familiarity with distributed systems, CI/CD workflows, or cloud-based research environments
- Knowledge of market microstructure or execution optimisation
