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G-Research

Quantitative finance research applying rigorous methods

Machine Learning Researcher

AI ResearchConfirmed live in the last 24 hours
Full-timeLondon, UKIn-person

About the Job

Requirements

  • A postgraduate degree in machine learning or a related discipline, or commercial experience developing novel machine-learning algorithms; exceptional success in online data-science competitions such as Kaggle will also be considered.
  • Experience in one or more of deep learning, reinforcement learning, non-convex optimization, Bayesian non-parametrics, natural-language processing, or approximate inference.
  • Strong reasoning skills and mathematical ability sufficient to develop models when off-the-shelf methods do not work.
  • Strong programming skills and experience working with Python, scikit-learn, SciPy, NumPy, Pandas, and Jupyter Notebooks.
  • Experience with object-oriented programming is beneficial.

Responsibilities

  • Investigate foundational questions, uncover market insights, and develop investment-management strategies using machine learning.
  • Use massive compute power and state-of-the-art machine-learning techniques to research quantitative-finance problems.
  • Develop and test machine-learning ideas with real-world data in an academic environment.
  • Read and discuss the latest machine-learning publications within the research community and attend leading conferences such as NeurIPS and ICML.

Desired Qualifications

  • Experience working with Python, scikit-learn, SciPy, NumPy, Pandas, and Jupyter Notebooks.
  • Experience with object-oriented programming.
  • Publications at top conferences such as NeurIPS, ICML, or ICLR.

About the Company

G-Research

Quantitative finance research applying rigorous methods

G-Research applies scientific rigour to solve complex challenges in financial markets. It brings together world-class researchers and engineers to develop data-driven models and trading ideas, testing them through rigorous experimentation and robust infrastructure. Unlike many traditional asset managers, its culture emphasizes deep exploration, reproducibility, methodical execution, and long-term thinking. The goal is to generate alpha through disciplined, evidence-based research that informs investment decisions and advances understanding of financial markets.

Company size
1,001-5,000
Company stage
Not listed
Total funding
Not listed
Headquarters
London, United Kingdom
Founded
2001

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