Stress Testing Manager

Overview

This role serves as a subject matter expert for enterprise stress testing and quantitative risk modeling. The position develops, implements, executes, enhances, and governs stress testing models used to assess risk primarily across the loan and deposit portfolios, with additional support for capital and liquidity stress testing.

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

Responsibilities

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.
• Stay current with evolving regulatory guidance and industry best practices related to stress testing, model governance, and quantitative risk management.

Collaboration and Communication

• Partner with Enterprise Risk Management (ERM), Credit Administration, Treasury, Finance, and Data Analytics teams to support enterprise risk initiatives.
• Provide independent challenge and critical review of analytical assumptions, scenario design, and model results.
• Prepare reports and presentations for management and various committees and sub-committees.
• Communicate complex quantitative concepts and analytical findings to both technical and non-technical audiences.

Requirements

• Bachelor’s degree in Statistics, Mathematics, Finance, Economics, Data Science, Financial Engineering, Computer Science, or a closely related quantitative discipline. (Master’s degree preferred)
• 5+ years of experience in quantitative risk analytics, stress testing, forecasting, model development, or portfolio analytics.
• Experience developing and implementing statistical or predictive models in banking, financial services, consulting, or risk management.
• Advanced proficiency in Python and SQL.
• Strong knowledge of statistical modeling, econometrics, forecasting, and quantitative risk methodologies.
• Experience working with large datasets and communicating complex findings to senior leadership.
• Experience with Power BI, Tableau, or similar visualization tools.

Preferred Qualifications

• Experience with Moody’s risk management, stress testing, or portfolio analytics solutions.
• Background in credit risk, commercial banking, or portfolio risk management.
• Experience supporting model validation, regulatory examinations, and audit activities.
• Knowledge of machine learning, cloud-based analytics platforms, and advanced quantitative techniques.
• Strong analytical and problem-solving abilities.
• Excellent communication and presentation skills.
• Ability to translate complex quantitative analysis into business recommendations.
• Proven ability to manage multiple priorities while maintaining strong governance and accuracy standards.

Compensation & Benefits

• Salary offered is based on factors including job duties, required qualifications, relevant experience, and local market trends.
• The role may be eligible for bonus or incentives based on company and individual performance.
• Base Pay Range: $92,000 - 120,000/year

Total Rewards may include a competitive benefits package with:

• 401(k) match, profit sharing, employee stock purchase plan
• Paid time off
• Medical, dental, vision
• Company-paid life insurance and long-term disability
• Supplemental voluntary life insurance
• Short-term and long-term disability
• Wellness incentives and an employee assistance program
• Pre-tax health savings accounts and flexible spending accounts (where eligible)

Location

Not specified in the provided job description.