Quantitative Researcher

Quantitative Research London, United Kingdom


Description

G-Research is a leading quantitative research and technology company. We use scientific techniques, big data and world-class technology to predict future movements in financial markets, and develop the platform to deploy these ideas globally. We offer a dynamic, flexible and highly stimulating environment where good ideas are prized and rewarded.

The Role


We research systematic investment 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 use the latest machine learning modelling techniques, robust statistical analysis and pattern recognition to analyse thousands of asset price time series, extracting deep insights from big data. Our core business is to try and 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. The exceptional intellectual standard of our research is made possible by our world leading simulation and back testing infrastructure, which uses advanced mathematical techniques and powerful software tools for portfolio construction and market microstructure analysis.

As a new joiner you will have a mentor to assist you to make the transition in to Quantitative Finance and learn the analytic techniques to carry out research. Once up and running, you will work in small teams developing ideas. This is a pure research role that would suit those who enjoy finding relationships in large data sets and working out how to interpret these results. We are not limited to price time-series data, but are interested in any data that is relevant to making better forecasts. Besides the data we already have in-house, we have the resources to purchase and clean new datasets if you have ideas which require something different: you are only limited by your imagination!

The Individual

  • You will need a strong background in mathematics.
  • A Masters or PhD degree in a highly quantitative subject (mathematics, statistics, computer science, physics or engineering) is desirable.
  • Previous financial experience is not required, although interest in finance and the motivation to rapidly learn more is a prerequisite for working here.
  • Since programming is an important part of the work, knowledge of numerical programming in an object-oriented language is useful.
  • Experience working with large data sets is also valuable.

What is essential is practical, hands-on ability to apply mathematical concepts to real world financial problems, to implement theoretical insights as working code, and the ability to work independently in a research environment

Compensation

Highly Competitive + Bonus