About the role
We 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 Responsibilities
* Design, analyse, and refine systematic trading strategies, primarily focused on derivatives (options, futures) with equity market exposure
* Apply deep understanding of volatility, Greeks, term structures, and risk to strategy development
* Conduct rigorous back-testing, validation, and performance analysis across historical and simulated data
* Work closely with AI, analytics and engineering teams to:
* Translate trading ideas into systematic, testable strategies
* Improve the quality, constraints, and evaluation of AI-generated strategies
* Contribute to the evolution of strategy pipelines, including documentation, testing standards, and deployment readiness
* Provide trading-domain input to ensure strategies are robust, interpretable, and suitable for live or simulated execution
* Support the scaling of the AI strategy function by embedding best practices from institutional trading environments.
Required experience
* Proven 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 Greeks
* Trade lifecycle and execution considerations
* Risk management and P&L attribution
* Advanced Python skills for quantitative research, analysis, and back-testing
* Experience working with large market data sets (historical and/or real-time)
* Ability to translate discretionary or conceptual trading ideas into systematic strategies
Working style & mindset
* Comfortable operating in an early-stage, build-mode environment
* No ego, highly collaborative, and happy working closely with engineers and researchers
* Able to work with ambiguity and help shape processes rather than wait for them
* Commercially minded, understands the difference between interesting research and deployable strategies
Nice to have
* Experience with options volatility trading or market-making concepts
* Exposure to AI-assisted research, machine learning models, or automated strategy pipelines
* Experience working across multiple asset classes, including crypto derivatives
* Familiarity with production trading systems or execution infrastructure.
Why join us
* Work at the intersection of institutional trading expertise and cutting-edge AI
* Direct influence on how strategies are designed, tested, and brought into production
* Close collaboration with senior technical and product leadership
* Opportunity to help shape a core function as the platform scales