Quantitative Researcher (Data Science/Machine Learning/Mathematical Modelling)
We research systematic trading ideas that predict the future of financial markets, applying scientific techniques to find patterns in large, noisy and rapidly changing real-world data sets. We are working on the fringes of the possible, trying to beat the efficient market hypothesis with the full “big data” tool set. We also build on the latest academic research into optimisation methods to find innovative solutions to the complexities that Markowitz ignored.
This is a pure research role where you will be able to develop and test your ideas with real-world data in an environment that resembles academia.
Machine Learning College
Machine Learning (ML ) College is G-Research’s new, in-house learning programme. Its aim is to develop those with requisite mathematical ability and underlying interest in machine learning into full-fledged ML experts through a world-class, custom curriculum. ML College will be available exclusively to new and existing Quantitative Researchers at G-Research, so if you join us in this role you’ll be able to take advantage of a learning experience tailored to accelerate your knowledge and expertise in machine learning quickly and effectively. Find out more about the G-Research ML College here.
Who are we looking for?
The ideal candidate will at minimum have experience in the following areas:
- You will have an interest in applying mathematical concepts to real world financial problems
- An interest in implementing theoretical insights as working code
- You will have, or be working towards gaining, a Masters or PhD degree in a highly quantitative subject (mathematics, statistics, computer science, physics or engineering)
- Previous financial experience is not required, although interest in finance and the motivation to rapidly learn more is a prerequisite for working here
Why should you apply?
- Highly competitive compensation plus annual discretionary bonus
- 9% company pension contribution
- Informal dress code and excellent work/life balance
- Comprehensive healthcare and life assurance
- 25 days holiday
- Contributory pension scheme
- Central London office close to 5 stations and 6 tube lines