Quantitative Researcher

3 days ago

London Area, United Kingdom Darcie Talent Full time

A leading algorithmic trading company driven by scientific research, data, and technology who build sophisticated models and systems that provide liquidity across global financial markets. Their teams combine deep quantitative expertise, world-class engineering, and a culture of rigorous experimentation.

Role Overview

You will lead original research in machine learning and artificial intelligence, developing methods that push the frontier of automated decision-making, prediction, and optimisation. You will have the freedom to pursue high-impact research questions, collaborate with other senior researchers and engineers, and drive innovations that directly influence trading performance and market understanding.

This role is ideal for experienced researchers who thrive at the intersection of theoretical insight and practical application.

Key Responsibilities

  • Lead cutting-edge research in areas such as deep learning, representation learning, reinforcement learning, probabilistic modelling, or generative modelling.
  • Design and implement scalable algorithms for forecasting, data assimilation, and high-dimensional optimisation.
  • Translate research ideas into production-ready systems, partnering with quantitative and engineering teams.
  • Mentor and guide junior researchers, fostering a culture of rigorous experimentation and reproducible science.
  • Evaluate emerging AI/ML methods and identify opportunities to apply them within their data and trading ecosystem.
  • Publish or present work internally and externally where appropriate, contributing to their visibility in the research community.

Qualifications

Required

  • PhD (or equivalent experience) in Computer Science, Mathematics, Physics, Statistics, or a related quantitative discipline.
  • Extensive track record of original research, demonstrated through publications in leading venues (e.g., NeurIPS, ICML, ICLR, AAAI)
  • Strong programming and algorithm-design skills, ideally in Python, C++ or JAX/TensorFlow/PyTorch.
  • Deep understanding of modern ML architectures, optimisation methods, and statistical learning theory.
  • Proven experience translating research into deployed solutions or high-impact prototypes.
  • Ability to operate autonomously and lead multidisciplinary collaborations.

Preferred

  • Prior experience in applied AI or research-driven industry settings (e.g., quantitative trading, tech research labs).
  • Familiarity with time-series analysis, sequential decision processes, or uncertainty quantification.
  • Experience managing or mentoring small research teams.
  • Interest in complex adaptive systems and data-driven decision-making under uncertainty.

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