Explore high-impact VP- CCAR/CECL Model Development & Monitoring Analytics jobs, a senior leadership niche at the intersection of advanced finance, statistics, and regulatory compliance. Professionals in this critical function are responsible for the end-to-lifecycle management of sophisticated quantitative models that forecast credit losses under both stressed economic scenarios (CCAR - Comprehensive Capital Analysis and Review) and current expected credit loss accounting standards (CECL). These models are fundamental to a financial institution's risk management, capital adequacy planning, and financial reporting, making this role strategically vital. A Vice President in this domain typically oversees two core pillars: development and monitoring. On the development side, they lead teams to design, build, and enhance econometric and statistical models that predict loan loss reserves and stress losses for various credit portfolios, such as consumer lending products. This involves deep analytical work, leveraging large datasets to identify macroeconomic and portfolio-specific drivers of credit risk. On the monitoring side, they establish robust frameworks for ongoing model performance tracking, annual model reviews, and validation support. This ensures models remain accurate, compliant, and fit-for-purpose amidst changing economic conditions and evolving regulatory expectations. Common responsibilities include managing stakeholder relationships with model developers, business lines, and internal validation teams; providing effective challenge to model assumptions and methodologies; and translating complex quantitative results into clear, actionable insights for senior management and regulatory presentations. Leadership is a key component, encompassing full management of a quantitative team, project management of multiple initiatives, and contribution to strategic, cross-functional risk governance programs. Typical skills and requirements for these executive jobs include an advanced degree (Ph.D. or Master's) in a highly quantitative field like Statistics, Economics, or Applied Mathematics, coupled with 10+ years of progressive experience in quantitative risk modeling within banking. Expertise in statistical programming (SAS, R, Python) and handling big data is essential, as is a thorough understanding of CCAR, CECL, and SR 11-7 model governance principles. The ideal candidate possesses exceptional communication skills to bridge technical and business audiences, proven project and people management capabilities, and a meticulous, detail-oriented approach to managing model risk. For those seeking to lead at the forefront of financial risk analytics, VP-level jobs in CCAR/CECL model development and monitoring offer a challenging and rewarding career path shaping the financial resilience of major institutions.
