“After nearly a year at G-Research, I’ve had the opportunity to contribute to the rapid growth of the Dallas team.
“I was given the freedom to build a high-performance, collaborative team by hiring top talent and developing effective training strategies and programmes, helping to expand our capacity to support a 24/7 production environment.
“We’re actively working on the latest AI and Machine Learning projects to stay ahead of industry standards. That’s why we have access to a wide range of training opportunities; for example, my entire team got AWS certified within a quarter.
“The best thing at G-Research is the ability to quickly bring ideas to life, embracing a culture of rapid innovation – fail fast, succeed faster and keep moving forward.”
"The friendly, collaborative atmosphere here is a breath of fresh air and a perfect fit for me."
"My favourite part of working for G-Research is that Technology is at the heart of everything we do at the company, driving the business forward and enabling us to stay ahead of the competition."
"The best thing about working at G-Research is being around such smart people, it motivates you to always want to grow and learn."
"The willingness to collaborate between both teams and functions has made the transition into my new role as easy as possible."
"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."
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 As technology evolves, outdated code becomes inefficient and harder to maintain.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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