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.

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.

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.

Inspirational Mathematicians

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.

G-Research and The Alan Turing Institute launch series of data science events

We are proud to announce that G-Research will be collaborating with The Alan Turing Institute to launch a lecture series on the subject of data science, its theories and applications.

Researchers from the Institute will deliver six technical talks on their research and ideas – ranging from machine learning and statistical methods to new ways to make sense of data. These will be available to the public on the the G-Research YouTube channel.

The talks will be delivered to G-Research employees, our partners in academia and Turing researchers.

Learn more about our interview process

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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