Quantitative Researcher – Machine Learning

About the role

We are looking for a Quantitative Researcher specialised in Machine Learning to build systematic trading models for digital assets and traditional financial markets. The position sits in the front‑office of a UK‑based trading team and offers direct exposure to high‑frequency market data and cutting‑edge ML techniques.

Key responsibilities

• Design and implement ML‑driven alpha generation models using high‑frequency order‑book and micro‑structure data.
• Develop and maintain robust data pipelines, preprocessing and feature‑extraction workflows for streaming tick data.
• Research, prototype and deploy advanced deep‑learning architectures for short‑horizon forecasting and signal extraction.
• Collaborate with quantitative researchers and engineers to integrate models into live trading systems, ensuring low inference latency and robustness.
• Continuously evaluate model performance through systematic back‑testing, live monitoring and iterative refinement.

Required profile

• Degree in Computer Science, Machine Learning, Applied Mathematics or a related quantitative discipline.
• Strong programming ability in Python and familiarity with common ML libraries.
• Proven experience applying ML/DL techniques to real‑world problems, preferably with time‑series or high‑frequency data.
• Experience building ML infrastructure such as data pipelines, experiment tracking and version control.
• Collaborative mindset with a problem‑solving orientation.

Required skills

• Python
• C++
• CUDA

What we offer

• Opportunity to work at the forefront of systematic trading and digital‑asset markets in the UK.
• Hands‑on exposure to large‑scale, high‑frequency data and state‑of‑the‑art ML methods.
• Merit‑based, technology‑driven team environment with direct impact on strategy performance.
• Competitive UK‑based compensation aligned with experience and results.