Join a leading team in Regulatory & Financial Risk as an Assistant Manager, Credit Risk Quant. This role focuses on the independent validation of critical credit risk models and ensuring regulatory compliance within a dynamic financial environment.

Deloitte's Strategy, Risk & Transaction group empowers clients to navigate risks and seize opportunities. We offer comprehensive risk services, from C-suite strategic planning to cyber threat management, supporting entities in achieving their value creation goals.

Perform in-depth validation of Advanced and Foundation IRB models, including PD, LGD, EAD, and CCF methodologies. Assess rating system design, performance, RWA attribution, and capital impact.

Evaluate model assumptions and methodologies for diverse wholesale exposures like corporate lending, project finance, CRE, and financial institutions. Review model conceptual soundness, data quality, risk differentiation, and calibration.

Challenge model segmentation, downturn calibration, collateral treatment, and default definitions. Ensure adherence to Basel III/IV IRB requirements and regional supervisory rules. Conduct rigorous model performance testing and prepare detailed validation documentation.

Support regulatory engagements, addressing model findings and audit requests. Collaborate with Model Development, Credit Policy, and Data Governance teams to ensure model fitness for purpose.

Required experience includes corporate lending, project finance, commercial real estate, and private equity exposures. Familiarity with stress testing frameworks (CCAR/ICAAP) and IRB-to-IFRS 9 model linkages is essential.

Possess the ability to articulate complex quantitative findings to non-technical senior stakeholders. Core competencies include an effective challenge mindset, high attention to detail, strong documentation discipline, and excellent stakeholder influencing skills.

Desired qualifications include experience in modeling or validation of Wholesale IRB capital models, IFRS9, or Climate Risk Modelling within large banking organizations. Strong technical proficiency in Python, R, SAS, and SQL is required, along with a solid understanding of credit modeling statistics.

Deep knowledge of IRB rating system architecture, Basel III/IV capital rules for wholesale credit, and model risk governance expectations (e.g., SR 11-7) is crucial. Strong analytical judgment and written communication skills are paramount.