Join EY's Financial Services Risk Management (FSRM) group as a Senior Consultant within the Quantitative Banking Book (QBB) team. This role involves supporting global financial institutions in managing various risks, including trading book market risk, counterparty credit risk, banking book credit risk, and operational risk. You will contribute to strategic transformations in risk management for the banking portfolio, applying quantitative skills to enhance risk estimation, ensure regulatory compliance, and develop analytics for improved client decision-making. This is an excellent opportunity for quantitative professionals interested in model development, regulatory initiatives, and high-impact capital markets engagements with leading financial institutions.

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Drive strategic and functional transformation within the banking portfolio's risk management. Enhance risk estimation processes and support regulatory compliance through advanced analytics. Develop data-driven insights to improve client decision-making, particularly for institutions with lending activities. Engage in model audits, validation, and development activities, demonstrating deep technical capabilities in financial products, especially lending products. Monitor project progress, manage risks effectively, and communicate status and priorities to stakeholders. Mentor junior consultants and review their completed tasks, ensuring high-quality deliverables. Stay abreast of market trends and client challenges within the financial services sector.

Requires a Master's degree in accounting, finance, economics, statistics, or a related field, along with at least 3 years of relevant work experience. Possess a comprehensive understanding of credit risk model development or validation for banking book portfolios (PD/LGD/EAD). Expertise in Stress Testing models is essential. Strong proficiency in data preparation, manipulation, and consolidation is crucial. Solid grounding in statistics and econometrics, including logistic and linear regression, is necessary. Demonstrate strong documentation skills for summarizing key details. In-depth knowledge of regulatory modelling (ECB/PRA/HKMA/Regulators) with model development/validation experience is required. Highly proficient in Advanced Python (Pandas, Numpy, ScikitLearn, OOP, Parallel Processing), SAS, R, SQL, and Excel. Awareness of emerging AI/ML methodologies in risk management and model validation is expected. Basic AI knowledge and excellent problem-solving skills are vital.