eFX Quantitative Researcher
eFX Quantitative Researcher
We are working with a leading global investment bank that is actively seeking an Electronic Trading Quant Researcher to join its FX Quant Trading & Research team. The team is responsible for developing cutting-edge electronic trading models across both Spot and Swaps, leveraging advanced statistical analysis, machine learning, and algorithmic research to enhance market-making and execution strategies.
This is a front-office role, offering direct exposure to traders, quantitative researchers, and technologists, working on the continuous enhancement of FX eTrading algorithms within a highly collaborative environment.
Key Responsibilities:
- Develop and enhance eTrading algorithms for Spot and Swap FX instruments, improving execution, pricing, and risk management strategies.
- Apply quantitative research, time-series analysis, and statistical modelling to extract insights and optimise electronic market-making strategies.
- Work alongside traders to refine fair value models, execution logic, and hedging strategies, with a strong focus on real-time market dynamics.
- Build and calibrate predictive models using alternative data sources, machine learning techniques, and flow analytics.
- Implement signal generation techniques to improve price prediction and liquidity capture across a wide range of FX instruments.
- Collaborate with technology teams to deploy models into production, ensuring performance and scalability within a high-frequency trading environment.
- Contribute to the continuous refinement of the bank's quantitative research and electronic trading infrastructure.
Key Requirements:
- 2-7 years of experience in quantitative research, algorithmic trading, or eTrading development within a bank, hedge fund, or proprietary trading firm.
- Strong background in FX markets, particularly electronic Spot and Swaps trading.
- Hands-on experience with statistical modelling, signal generation, and execution optimisation.
- Proficiency in Python, R, or kdb/q for research and analysis.
- Experience coding in a shared codebase and working in a collaborative development environment.
- Knowledge of Java, C++, or similar low-latency programming languages for algo implementation is highly desirable.
- Strong understanding of financial market structure, liquidity dynamics, and execution strategies.
- Excellent communication skills, with the ability to present research ideas and collaborate across teams.
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