Quantitative Researcher – Machine Learning (UK)

We are seeking a talented Quantitative Researcher to develop machine learning-based models for systematic trading in digital asset and financial markets. This is a front-office research role based in the UK, offering hands-on experience with high-frequency market data, advanced ML architectures, and collaboration with a team of quantitative researchers and engineers.

Responsibilities

1. Develop ML-based alpha generation models using high-frequency order book and market microstructure data
2. Design and maintain robust data pipelines, preprocessing, and feature extraction workflows for streaming tick data
3. Research and implement advanced deep learning architectures for short-horizon forecasting and signal extraction
4. Collaborate with quantitative researchers and engineers to integrate models into live trading systems
5. Optimise inference latency and ensure model robustness under live market conditions
6. Continuously refine model performance through systematic backtesting, live evaluation, and monitoring

Requirements

1. Degree in Computer Science, Machine Learning, Applied Mathematics, or a related quantitative discipline
2. Strong programming skills in Python and familiarity with standard ML libraries
3. Proven experience applying ML/DL techniques to real-world problems
4. Familiarity with time-series modelling, signal extraction, or high-frequency data
5. Experience developing ML infrastructure, including data pipelines, experiment tracking, and version control
6. Collaborative mindset and problem-solving orientation

Preferred Experience

1. Exposure to finance, trading, or quantitative research (helpful but not required)
2. Publications, competition results (e.g., Kaggle, academic ML contests), or open-source contributions
3. Familiarity with C++, CUDA, or other low-latency systems

Why Join

1. Work at the forefront of systematic trading and digital asset markets in the UK
2. Hands-on exposure to large-scale, high-frequency data and cutting-edge ML techniques
3. Collaborative, meritocratic team environment with direct impact on strategy and performance
4. Fast-paced, technology-driven culture offering meaningful ownership and growth
5. Competitive UK-based compensation aligned with experience and performance