“My job is to find market patterns and use those to forecast future market movements. The core part of it is finding what we call signals, that build on some insight or model to predict the market.
“G-Research makes a lot of effort to have a very open culture and gives a lot of freedom to its individual researchers to pursue directions that they think are valuable, with each researcher very much driving their own research. I didn’t feel like I was losing a lot of freedom (compared to academia) in that aspect.
“We have tight integration with Engineering, and my team has embedded engineers working with us directly on the same projects. This is very helpful, because it means that you have people from slightly different backgrounds coming together, covering both the Software Engineering and the Quantitative Research side, to solve difficult problems.”
"My favourite thing about working at G-Research is the people. G-Research strives to hire not only the brightest minds, but good people, which in turn creates a brilliant collegiate and social atmosphere at the company."
"My favourite part of working at G-Research is the people, from my colleagues to our customers. The culture is great and encourages collaboration, which makes it easier for everyone to work together. It’s also great to be able to use the latest tech, like Kubernetes and Kafka."
"What I appreciate most about working in G-Research is the supportive and knowledgeable environment. Everyone is incredibly helpful and patient, which ensures there’s a good balance between being challenged and your workload."
"There are lots of people within the business that have started as a junior and progressed – which I think is testament to G-Research’s belief in fostering growth and recognising potential."
"The two biggest things that I like about working at G-Research are the smart and incredibly friendly colleagues, as well as being able to strike a really good work-life balance (in contrast to a lot of the finance industry)."
Hear from our Head of Forecasting Engineering on why the term "tech debt" has outlived its usefulness. In this blog, he explores why we should move away from generic labels and instead ask more precise, value-driven questions that lead to meaningful improvements in engineering and business outcomes.
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Each month, we provide up to £2,000 in grant money to early career researchers in quantitative disciplines. Hear from our March grant winners.
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Hear from Jay, an Open Source Software Engineer, on tackling technical debt in OpenStack. As technology evolves, outdated code becomes inefficient and harder to maintain. Jay highlights the importance of refactoring legacy systems to keep open-source projects sustainable and future-proof.
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