Quantitative Researcher in Machine Learning

Quantitative Research London, United Kingdom


The Role

Our Quantitative Researchers explore systematic investment ideas to predict the future behaviour of financial markets, applying a rigorous scientific methodology to find signals in large, noisy and rapidly changing real-world data sets. Machine learning expertise is business-critical for the firm and it is essential that we remain at the cutting edge: You will use the latest techniques in the field to extract deep insights from big data.

Similarly to a post-doc position, you will work on a small number of projects concurrently, extending classical methods and developing entirely novel ideas; you will read the latest publications in the field, discuss them within the firm's research community, and attend the leading conferences worldwide. There is never a need to be reactive: there are separate teams dealing with day-to-day maintenance issues to allow you an exclusive focus on research. You will usually implement your own models, and you will need to understand their theoretical foundations in order to apply them successfully to our uniquely challenging data sets.

The Individual

  • Strong interest in practical and theoretical machine learning is essential: either a post-graduate degree in ML or related discipline, or commercial experience developing novel ML algorithms; we will also consider exceptional candidates with a proven record of success in online data science competitions (e.g. Kaggle).
  • Experience with object-oriented or functional programming is highly desirable: you will be developing your own models and need to operate with our existing codebase.
  • Excellent reasoning skills and mathematical ability are crucial: the textbook methods rarely work on our data, and you will need to understand how to fix them.
  • Successful applicants have demonstrated expertise in neural networks and deep learning; non-convex optimisation; Bayesian non-parametrics and approximate inference. The list is not exhaustive: we hire the most talented candidates from the widest range of backgrounds in the field.

Highly Competitive + Bonus