G-Research is one of Europe’s leading quantitative finance research firms. We hire the brightest minds in the world to tackle some of the biggest questions in finance. We pai this expertise with machine learning, big data and some of the most advanced technology available to predict movements in financial markets.
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.
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 (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.
The ideal candidate will at minimum have experience in the following areas:
G-Research is committed to cultivating and preserving an inclusive work environment. We are an ideas-driven business and we place great value on diversity of experience and opinions.
We want to ensure that applicants receive a recruitment experience that enables them to perform at their best. If you have a disability or special need that requires accommodation please let us know in the relevant section.
Learn moreG-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.
Typically, G-Research hires PhD-level mathematicians and gives them access to extensive data and an advanced platform to enable them to predict movements in financial markets.
But we are looking to change things up. We are hiring an experienced Quantitative Analyst with strong knowledge of financial markets and solid understanding of data interrogation and the mathematical principles underpinning this.
Using your financial knowledge and analytical skills, you will help to build mathematical models of price movements based on a broad array of data inputs.
We are seeking individuals with a passion for, and keen interest in, financial markets. The ideal candidate will have solid quantitative and computing skills, backed up by a strong background in fundamental equity research.
For example, this might be someone already working in the discretionary space who enjoys the mathematical and data side of things, and is interested in making the step across into the quantitative world.
In particular, we want to hear from highly motivated candidates with the following skills and experience:
G-Research is committed to cultivating and preserving an inclusive work environment. We are an ideas-driven business and we place great value on diversity of experience and opinions.
We want to ensure that applicants receive a recruitment experience that enables them to perform at their best. If you have a disability or special need that requires accommodation please let us know in the relevant section.
Learn more