About the roleWe are looking for a Quantitative Researcher with strong derivatives and equity trading desk experience to join our growing analytics function.This role has been created to strengthen domain depth within the team and to support the next phase of development of our AI-driven trading platform and proprietary trading business. You will work closely with engineers and researchers to design, evaluate, and deploy systematic trading strategies, with a particular focus on derivatives.This is a hands-on role suited to someone who has operated in institutional trading or quantitative research environments and is comfortable moving between market intuition, data, and production-grade systems.Core ResponsibilitiesDesign, analyse, and refine systematic trading strategies, primarily focused on derivatives (options, futures) with equity market exposureApply deep understanding of volatility, Greeks, term structures, and risk to strategy developmentConduct rigorous back-testing, validation, and performance analysis across historical and simulated dataWork closely with AI, analytics and engineering teams to:Translate trading ideas into systematic, testable strategiesImprove the quality, constraints, and evaluation of AI-generated strategiesContribute to the evolution of strategy pipelines, including documentation, testing standards, and deployment readinessProvide trading-domain input to ensure strategies are robust, interpretable, and suitable for live or simulated executionSupport the scaling of the AI strategy function by embedding best practices from institutional trading environments.Required experienceProven experience working with derivatives (options, futures, structured products)Prior experience on or closely aligned to an equity trading desk (buy-side or sell-side)Strong understanding of:Volatility surfaces and GreeksTrade lifecycle and execution considerationsRisk management and P&L attributionAdvanced Python skills for quantitative research, analysis, and back-testingExperience working with large market data sets (historical and/or real-time)Ability to translate discretionary or conceptual trading ideas into systematic strategiesWorking style & mindsetComfortable operating in an early-stage, build-mode environmentNo ego, highly collaborative, and happy working closely with engineers and researchersAble to work with ambiguity and help shape processes rather than wait for themCommercially minded, understands the difference between interesting research and deployable strategiesNice to haveExperience with options volatility trading or market-making conceptsExposure to AI-assisted research, machine learning models, or automated strategy pipelinesExperience working across multiple asset classes, including crypto derivativesFamiliarity with production trading systems or execution infrastructure.Why join usWork at the intersection of institutional trading expertise and cutting-edge AIDirect influence on how strategies are designed, tested, and brought into productionClose collaboration with senior technical and product leadershipOpportunity to help shape a core function as the platform scales