Quantitative Researcher (New Ventures)
G-Research is Europe’s leading quantitative finance research firm. We hire the brightest minds in the world to tackle some of the biggest questions in finance. We pair this expertise with machine learning, big data, and some of the most advanced technology available to predict movements in financial markets.
The Opportunities Evaluation Group (OEG) is an exciting new team at G-Research that sits alongside our core Research function. Its remit is simple: to do the impossible.
While Research is a world-class, large-scale operation with established approaches and technologies, not all problems fit nicely into one framework.
OEG’s approach, therefore, is different. Starting with the core principle is that any problem is fair game, it is our job to prioritise ideas outside the business’s current capabilities and then demonstrate the value by building proof-of-concept systems which can later be integrated.
OEG need to move fast and discount bad ideas quickly. We do this using a small team of highly talented individuals working closely together and using the best new technology to give us a head-start. Being small means we can be nimble, changing our approaches and our tools to suit the problem in front of us but never compromising on the rigour of our scientific method.
Who are we looking for?
OEG looks for the very best Quants and Engineers to assist with its mission. Our preferred candidates are those with a strong mathematical background who can perform across a broad set of problems (“T-shaped” people). We like Quants who have a greater-than-average exposure to technology and coding, because we need to build the Research systems as well as use them. Above all, we want innovators and critical thinkers.
The ideal candidate will at minimum have strong interest or experience in the following areas:
- Applying mathematical concepts to real-world (financial) problems
- Implementing theoretical insights as working code
- A Masters or PhD degree in a highly quantitative subject (Mathematics, Statistics, Machine Learning, Computer Science, Physics) – either complete or currently working towards
- 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
- Informal dress code and excellent work/life balance
- Comprehensive healthcare and life assurance
- 25 days holiday
- Pension with 9% company contribution
- Cycle-to-work scheme
- Subsidised gym membership
- Monthly company events
- Central London office close to 5 stations and 6 tube lines