Quatitative Anaylst Equity Derivatives London

We are seeking a highly skilled Quantitative Analyst to join our Front Office team within a Tier 1 bank in London, focusing on equity pricing, including auto callable, options, light exotics, and stochastic volatility modelling. This position will involve close interaction with traders in a fast-paced environment, developing bespoke models for equity pricing. The successful candidate will design, develop, implement, and support mathematical, statistical, and machine learning models to enhance business decision-making.

We are looking for someone who has come from a front office desk at a competitor. Ideally, at the senior end of Associate. The team are set up in a way to which this individual will grow into a VP in the near future. The person we are looking for is someone who can communicate well with the business, and also have the market intuition to make meaningful suggestions to trading. We are looking for someone who can confidently take ownership of their work, drive results, and make a meaningful impact within the team.

Responsibilities
* Design and develop analytics solutions and collaborate to identify dependencies, such as data requirements and tools, for successful implementation.
* Implement and operationalise models whilst also using analytics and models and create well-tested, stable software, and ensure accurate, reliable, and efficient deployment of solutions.
* Effectively build high-quality pricing analytics for equity derivative products. Including auto-callables, equity options and light exotics.
* Frequent interaction with the business and building of state of the art trader tools.

Requirements
* Proven experience in designing, developing, and implementing mathematical, statistical, and machine learning models, including quantitative research, and modelling specifically within equities, auto cables and light exotic options.
* Ability to work collaboratively with cross-functional teams and communicate complex analytical concepts to stakeholders.
* Understanding of risk and governance frameworks, with the ability to identify risks, develop policies, and manage compliance with enterprise risk management policies.
* Proficiency in programming languages such as C++, Python, and other domain-specific tools relevant to quantitative finance.