Join EY's Financial Services Risk Management (FSRM) group as a Senior Consultant within the Quantitative Banking Book (QBB) team. This role offers a unique opportunity to support global financial institutions in managing complex risks, including trading book market risk, counterparty credit risk, and banking book credit risk. You will drive strategic and functional transformation in risk management by applying quantitative skills to enhance risk estimation, ensure regulatory compliance, and develop analytics for better decision-making in lending activities. This is an ideal position for quant professionals seeking to engage with advanced models, regulatory initiatives, and high-impact capital markets engagements.

Key responsibilities include leveraging deep technical expertise and industry knowledge of financial products, particularly lending products. You will stay informed about market trends and client challenges within the financial services sector. Effective stakeholder communication regarding progress, risks, and priorities is essential for achieving project outcomes. This role also involves mentoring junior consultants and reviewing their completed tasks.

Furthermore, you will actively participate in model audits, validation, and development activities, demonstrating flexibility across diverse projects. The position requires a thorough understanding of credit risk model development or validation for the banking book portfolio (PD/LGD/EAD), along with hands-on experience in data preparation and manipulation. Expertise in Stress Testing models is also a crucial aspect of this role.

Successful candidates will possess a postgraduate degree (Master's in accounting, finance, economics, statistics, or a related field) and at least three years of relevant work experience. Strong knowledge of regulatory frameworks such as IFRS 9, IRB, CCAR, CECL, Stress Testing, and DFAST is required. Proficiency in advanced Python (Pandas, Numpy, Scikit-Learn, OOP, Parallel Processing), SAS, SQL, R, and Excel is essential.

We are looking for individuals with a solid grounding in statistics and econometrics, including logistic regression, linear regression, fractional response, and decision trees. Excellent documentation skills, the ability to grasp key details quickly, and summarize them effectively are vital. Experience with regulatory modelling and a basic understanding of AI/ML methodologies in risk management are also key. Initiative, independence, and strong analytical and problem-solving skills are expected.