Embark on a significant career opportunity within EY's Financial Services Risk Management (FSRM) group. This role involves supporting premier global financial institutions in managing diverse risks, including trading book market and counterparty credit risk, banking book credit risk, operational risk, and regulatory compliance. As part of the Quantitative Trading Book (QTB) team, you will drive strategic and functional transformations across risk, treasury, and front-to-back office operations.

Utilize advanced quantitative skills to enhance risk and valuation processes, ensure regulatory adherence, and develop analytics that empower informed decision-making for clients engaged in capital markets activities. This is an ideal position for quant professionals seeking to engage with cutting-edge models, regulatory initiatives, and impactful capital markets projects for major global banks, broker-dealers, asset managers, and insurance firms.

Key responsibilities include demonstrating profound technical expertise and industry insights into financial products. You will lead significant client engagements or manage smaller projects, consistently delivering high-quality client services. Stay informed about market trends and client challenges within the financial services sector.

Effectively manage risks and maintain clear communication with key stakeholders regarding project status, issues, and priorities to achieve desired outcomes. You will be responsible for strategic decision-making, process optimization, resource allocation, and team supervision to ensure successful task execution and performance alignment with organizational objectives.

Success in this role requires a strong command of statistical and numerical techniques, such as Monte Carlo simulations and finite difference methods. A solid understanding of derivative pricing concepts across various asset classes (rates, equities, credit, FX, commodities) is essential.

Possess a robust foundation in mathematical principles, including stochastic calculus, differential and integral calculus, probability, and linear algebra. Familiarity with optimization techniques, particularly gradient-based methods, for calibration, risk analytics, and numerical model implementation is expected. Experience in model development, validation, monitoring, and audit procedures for trading book models is crucial.

Proficiency in advanced Python/C++ coding and basic SQL is mandatory. Awareness of emerging AI/ML methodologies and their application in risk management, model validation, and quantitative workflow automation is highly valued. Exceptional communication, analytical thinking, and problem-solving skills are paramount.