Quant Analyst

Job Title: Quant Analyst – Equity Derivatives | Contract | Hybrid London Location: London (2 days onsite, 3 remote) Type: Contract (6 months, likely extension) Rate: Market Competitive (Inside IR35) Start Date: ASAP Overview: An exciting opportunity to join a global investment bank\’s Quantitative Analytics team focused on Equity and Hybrid Derivatives. The role involves supporting and improving internal risk models impacting front-office and risk teams, particularly for complex equity-linked products. This is ideal for someone with deep quantitative finance knowledge, strong C++/Python skills, and experience in derivatives modelling. Key Responsibilities: * Support and improve internal risk models related to CVA for equity/volatility products (e.g. Corridor Variance Swaps) * Document and test model outputs with a high degree of accuracy * Liaise with front office, tech, and model validation teams to ensure successful production deployment * Communicate complex model results to stakeholders across quant, trading, and risk Skills & Experience Required: * Master’s or PhD in Mathematics, Computer Science, or related field * Strong foundation in financial mathematics and derivatives pricing * Professional experience in front office or risk quant roles * Proficiency in Python and C++ (especially in shared library development) * Experience building numerical algorithms for financial use cases * Excellent written and verbal communication skills, especially in stakeholder-heavy environments Nice to Have: * Previous exposure to structured or hybrid equity products * Experience working with cross-asset or quantitative strategy teams * Ability to work independently in a fast-paced, regulated environment * An interest in model governance, compliance, and process robustness Why Join This Project? * Contribute to high-impact equity derivatives risk models used globally * Partner directly with front-office traders and quantitative teams * Grow your skills with exposure to modern tools and model deployment pipelines