Machine Learning Researcher

2 months ago

London, Greater London, United Kingdom G-Research Full time

G-Research is a leading quantitative research and technology firm that empowers its team to tackle the biggest questions in finance with unparalleled computing power. We value innovation and talent, fostering a dynamic and stimulating culture that cultivates world-beating ideas.

This role is based in our Soho Place office in Central London, where our Research Lab is located. As a member of our team, you will work with massive datasets and cutting-edge ML techniques to develop successful investment management strategies.

  • You will harness the power of massive compute resources to disprove the efficient market hypothesis, using state-of-the-art ML methods to stay ahead of the competition.
  • Our team's core drivers of performance and success rely heavily on ML, which has been a key tool at G-Research for years. You will work with a range of ICML and NeurIPS published researchers and contribute to the development of novel machine learning algorithms.
  • With huge amounts of clean data and near-instant feedback, you will be incentivized to explore the cutting-edge and find the 1% of difference that drives our success.
  • You will be part of a vibrant, collaborative research community that stays up-to-date with the latest publications in the field and attends leading conferences worldwide, such as NeurIPS and ICML.
  • This research role offers the opportunity to develop and test your ideas with real-world data in an academic environment, with the potential to make a significant impact on the business.
Requirements
  • A post-graduate degree in machine learning or a related discipline, or commercial experience developing novel machine learning algorithms. We also consider exceptional candidates with a proven record of success in online data science competitions, such as Kaggle.
  • Experience in one or more of deep learning, reinforcement learning, non-convex optimisation, Bayesian non-parametrics, NLP, or approximate inference.
  • Excellent reasoning skills and mathematical ability are crucial, as off-the-shelf methods may not work on our data, and you will need to understand how to develop your own models.
  • Strong programming skills and experience working with Python, Scikit-Learn, SciPy, NumPy, Pandas, and Jupyter Notebooks are desirable. Experience with object-oriented programming is beneficial.
  • Publications at top conferences, such as NeurIPS, ICML, or ICLR, are highly desirable.
What We Offer
  • Highly competitive compensation plus annual discretionary bonus.
  • Lunch provided via Just Eat for Business and a dedicated barista bar.
  • 35 days' annual leave.
  • 9% company pension contributions.
  • Informal dress code and excellent work/life balance.
  • Comprehensive healthcare and life assurance.
  • Cycle-to-work scheme.
  • Monthly company events.

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