“I joined G-Research in 2021, as a Quantitative Researcher in the NLP team, after completing my PhD in Natural Language Generation at Sorbonne Université.
“My role focuses on finding signals in real-world data and in many ways, it feels like a continuation of my PhD; I’m looking at unexplored problems and I choose which ones to focus on.
“Where it improves on my PhD is the fact that I don’t work in isolation. I can share ideas with other quants, engineers and data scientists, I get access to very interesting datasets and a lot of compute to help me deliver on my ideas.”
"What I like the most about my job is it’s super open. I’m able to work with a lot of folks from other teams, too, such as working closely with Engineers and other Quantitative Researchers."
"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."
"My intern experience was really good. You get the opportunity to impact a business, which is important if you’re preparing to enter the workplace. You get to do something useful and see how it gets used; I worked on a project that is still being used now."
"Work culture is an important aspect for me, so when I was contacted by G-Research I discovered a company where I could grow as a developer, whilst feeling like the company valued me as a person, not just a code monkey."
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 As technology evolves, outdated code becomes inefficient and harder to maintain.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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