Job Specifications
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