Stress Testing Manager

The Stress Testing Manager serves as a subject matter expert for enterprise stress testing and quantitative risk modeling. This role is responsible for the development, implementation, execution, enhancement, and governance of stress testing models used to assess risk primarily across the loan and deposit portfolios, but also provides key support for capital and liquidity stress testing processes. The position will leverage both third-party solutions, including Moody’s analytical platforms, and internally developed models to evaluate the impact of adverse economic conditions on portfolio performance and emerging risk exposures.

Working within the Second Line of Defense (SLOD), the Stress Testing Manager provides independent challenge to assumptions, methodologies, and model outputs while supporting the Bank's Enterprise Risk Management framework. This individual will partner closely with Credit, Finance, Treasury, Model Risk Management, and Enterprise Risk Management teams to ensure stress testing practices remain robust, analytically sound, and aligned with strategic and regulatory expectations.

The role requires a highly analytical and inquisitive professional with significant quantitative modeling experience, strong statistical expertise, and the ability to communicate complex analytical concepts to senior management.

Stress Testing and Scenario Analytics

• Lead the execution, enhancement, and ongoing administration of enterprise loan portfolio stress testing programs.
• Utilize and maintain third-party stress testing solutions, including Moody’s risk and portfolio analytics platforms.
• Develop and implement proprietary stress testing methodologies for specialized segments of the loan portfolio.
• Design and execute scenario analyses, sensitivity analyses, and adverse economic stress tests to evaluate portfolio vulnerabilities.
• Translate macroeconomic assumptions into expected portfolio performance outcomes, including credit quality deterioration, migration trends, and expected loss projections.
• Identify emerging portfolio risks and communicate key findings to management through meaningful analytics and reporting.
• Apply advanced quantitative techniques including regression analysis, time-series forecasting, machine learning methods, Monte Carlo simulation, and scenario analytics.
• Perform data analysis and model development using Python, SQL, and other analytical tools.
• Evaluate model performance through back-testing, benchmarking, sensitivity testing, and ongoing performance monitoring.
• Continuously enhance methodologies to improve predictive accuracy and analytical value.

Deposit and Liquidity Risk Analytics

• Assist in the development of stress testing methodologies for deposit portfolios and funding stability analysis.
• Support Enterprise Risk Management (ERM), Treasury, and Finance teams by providing analytical insight related to liquidity stress scenarios and deposit behavior under stressed conditions.
• Work with Financial Risk Management (FRM) to develop quantitative approaches to evaluate deposit concentration, attrition, runoff assumptions, and customer behavior across economic cycles.

Governance and Model Risk Management

• Maintain comprehensive model documentation, methodology documents, assumptions inventories, and supporting analytical materials.
• Support Model Risk Management activities by ensuring models adhere to established governance standards and validation requirements.
• Assist independent validation efforts through development of documentation, data support, model inventories, and performance monitoring results.
• Establish controls and monitoring processes designed to ensure model integrity, data quality, and analytical consistency.
• Maintain awareness…