Charles Levick Limited
Senior Quantitative Developer / Researcher
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Charles Levick have partnered with a leading proprietary High Frequency Trading firm undergoing significant growth across its platform.
High Frequency Trading | Equities & FX | London
We’ve been exclusively mandated to find a high-calibre Senior Quant Developer / Researcher to take ownership of designing, developing and deploying alpha-generating trading strategies across high-frequency Equities and FX markets.
This is a role for someone who wants real autonomy, capital backing, and the ability to scale a strategy, not just manage risk within tight constraints.
Key Responsibilities
- Research and develop systematic trading strategies across Equities and FX markets.
- Design predictive models using large-scale market and alternative datasets.
- Build robust research infrastructure and quantitative libraries.
- Develop ultra-low latency models suitable for live trading environments.
- Analyse order book dynamics, execution quality and market microstructure.
- Backtest, validate and optimise systematic trading strategies.
- Work closely with traders and technology teams to deploy production-ready models.
- Continuously improve existing strategies through statistical analysis and machine learning techniques.
- Monitor live performance and identify opportunities to improve profitability.
- Contribute new ideas for alpha generation across global electronic markets.
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What We’re Looking For
- Strong academic background in Mathematics, Statistics, Physics, Computer Science, Engineering or a related quantitative discipline.
- Experience developing High Frequency Trading (HFT) strategies.
- Proven experience working within a proprietary trading firm, hedge fund or HFT environment.
- Demonstrable experience researching or developing systematic strategies across Equities or FX.
- Excellent understanding of market microstructure and electronic trading.
- Strong programming skills in Python and C++ (or equivalent low-level language).
- Experience working with large financial datasets and statistical modelling.
- Strong knowledge of probability, optimisation, stochastic processes and machine learning techniques.
- Experience building scalable research tools and production systems.
- Ability to independently generate research ideas and validate hypotheses.
- Excellent communication skills with the ability to collaborate across research, trading and engineering teams.
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