Company: A leading quantitative hedge fund specialising in high-frequency strategies across global equities, futures, and options markets.
Location: London, United Kingdom.
Brief: The firm is a building a specialist, ML-driven HFT team covering equity and futures markets.
Responsibilities:
* Design, build, and backtest machine learning models to generate alpha in low-latency settings.
* Work closely with infrastructure and execution teams to integrate models into production.
* Engage in data engineering and feature engineering: sourcing, cleaning, and transforming vast streams of market/alternative/microstructure/tick-level data.
* Develop strategies that adapt to market microstructure dynamics (e.g. order flow, market impact, latency arbitrage, predictive of short-term price movements).
* Conduct rigorous risk assessments and monitor/maintain live performance.
Requirements:
* Advanced degree (PhD/MSc) in a quantitative discipline: Mathematics, Physics, Statistics, Computer Science, or similar.
* Strong background in machine learning, deep learning, and statistical modelling (e.g., gradient boosting, neural networks, reinforcement learning).
* Proficiency in Python, C++, and high-performance computing environments.
* Experience with financial time-series analysis, market microstructure, or electronic trading preferred.