Quantitative Research

Quantitative Research

We use the latest scientific techniques and advanced data analysis methods to discover the undiscovered. Our researchers are free to explore ideas, finding patterns in large, noisy and real-world data sets to predict the movements in global financial markets.

Machine Learning

We employ cutting edge machine learning methods drawn from diverse areas such as neural networks and deep learning; non-convex optimisation; Bayesian non-parametrics and approximate inference. We have the freedom to extend classical methods as well as develop entirely new ideas.

Quantitative Research

Our technology, research and resources are combined to build a single, powerful platform for developing your ideas. We use rigorous scientific methodology, robust statistical analysis and pattern recognition to analyse an extensive and varied financial data ecosystem, extracting deep insights from truly massive datasets. Our platform provides the ability to test your mathematical models in action and get instant results using real world data.

Inspirational Mathematics

At G-Research we promote an academic and intellectual culture. Most of our Researchers have joined from PhDs or Postdocs from top-tier global institutions. There are multiple IMO medallists, Fulbright Scholars and even a Senior Wrangler.

IMO 2019

We are proud to be a gold sponsor of the International Mathematical Olympiad 2019 which will be held the United Kingdom.

More information to come on this soon!

What we look for

You’ll have a record of academic achievement in mathematics, physics, machine learning, computer science or engineering.

There’s no need for experience in finance.

Interview process

You’ll take a 90 minute, handwritten technical test to demonstrate excellence in maths, stats, programming and probabilities. This is followed by interviews.

The assessment process is highly challenging, however, no prior preparation is required. You can get an idea of what to expect by reviewing our suggested reading list and attempting our sample test questions

Suggested Reading

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Sample questions

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