Quantitative Developer

fingertips to achieve our aim: predicting the future.The core tech stack is C# and Python, productionised in our own datacentres. Areas of focus for these teams include:Trading systems - reliable and performant systems able to trade 24/6 for our customers, with real money at stakeModelling - building core capabilities and assisting quant researchers in our cutting-edge prediction capabilitiesSimulation - back-testing frameworks for validating the strategies our researchers produce and for assessing their ongoing performanceResearch tooling - front-end UX and workflow for our quant researchersPerformance and scalability - optimising our trading and research systems to unlock new capabilitiesTo give a flavour of the work we do, here are some of our recent projects:Low level performance optimisations in our core simulation engine, unlocking the next advances in quant researchExperimenting with alternative solvers in a core trade planning systemIntegrating our high and low frequency

systems for more optimal tradingRe-architecting systems to provide a seamless path from research to production for machine learning modelsEnabling large-scale distributed training of machine learning modelsContributing back to open source projectsWho are we looking for? The ideal candidate will:Deliver high-quality, well-engineered software with strong architectural awarenessTake end-to-end ownership of solutions, from concept to deliveryDemonstrate solid knowledge of algorithms, data structures, and software fundamentalsShow interest in quantitative finance and the role of engineering within itPrioritise effectively to deliver measurable business impactProactively, identify and implement scalable improvementsStay ahead of emerging technologies and drive their adoptionApply sound judgment and balance competing approachesCommunicate clearly and adapt their style to different audiencesUnderstand others’ needs to deliver mutually beneficial outcomesCollaborate effectively and build strong

relationships across the businessWhy, should you apply? Highly competitive compensation plus annual discretionary bonus Lunch provided (via Just Eat for Business) and dedicated barista bar 35 days’ annual leave 9% company pension contributions Informal dress code and excellent work/life balance Comprehensive healthcare and life assurance Cycle-to-work scheme Monthly company events G-Research is committed to cultivating and preserving an inclusive work environment. We are an ideas-driven business and we place great value on diversity of experience and opinions. We want to ensure that applicants receive a recruitment experience that enables them to perform at their best. If you have a disability or special need that requires accommodation please let us know in the relevant section At G-Research, we are passionate about the intersection of finance, technology, and the future. We offer a dynamic, flexible and highly stimulating culture where world-beating ideas are cultivated and rewarded. We are proud to employ some of the best people in their field and to nurture their talent in our collaborative working environment. #J-18808-Ljbffr

OverviewWe tackle the most complex problems in quantitative finance, by bringing scientific clarity to financial complexity. From our London HQ, we unite world-class researchers and engineers in an environment that values deep exploration and methodical execution - because the best ideas take time to evolve. Together we’re building a world-class platform to amplify our teams’ most powerful ideas. As part of our engineering team, you’ll shape the platforms and tools that drive high-impact research - designing systems that scale, accelerate discovery and support innovation across the firm. Take the next step in your career. The role Engineering underpins our continued growth and success, and we are committed to recruiting and developing the world’s best Engineers. Our Quantitative Developers are the enablers of our success. They work side-by-side with our researchers to realise their ideas in global financial markets. They work at the bleeding-edge with immense compute power at their