VP, Operational Risk Model Developer (Hybrid)

Operational Risk Management (ORM) is looking to add a model developer to the Operational Risk Quantification Team. The Operational Risk Quantification Team is responsible for models that assist management in understanding and quantifying operational risks and meet the needs of the regulatory community (e.g., Basel, ICAAP and CCAR). Operational Risk is a critical and important risk type that is receiving increased focus, particularly after the large losses suffered by the industry over the years following the financial crisis. It is a particularly interesting and challenging risk to quantify, given the diversity of the risks and the potential for large losses. A combination of qualitative (e.g. scenario analysis) and mathematical modeling approaches are used.

The position requires a strong balance of quantitative skills, an ability to understand the practical business context, and written and oral communication skills. We value domain experience but are most focused on candidates with a strong underlying skill set who can learn quickly and advance in responsibility.

Description:

• Work with colleagues in Risk Management to understand the drivers of losses and the business context to improve the design of the analytics.
• Develop stress loss models for operational risk models, including regulatory capital models and CCAR models.
• Leverage knowledge of risk assessment, risk monitoring and risk models and techniques to develop, test, document, and enhance portfolio models, visualization and diagnostic tools for testing model robustness, stability and performance.
• Research and analyze financial loss data, and issue special reports identifying risk drivers, estimating financial risk and measuring model risk.
• Develop and maintain clear documentation for methodologies and applications; including project plans, model descriptions, mathematical derivations, data analysis, process and quality controls.
• Support the implementation of analytical tools by reporting functions, and the migration of models to the production environment. Facilitate cross-functional dialogue with business and clients to improve risk reporting and internal and external regulatory compliance.
• Actively participate in the analysis and interpretation of results, incorporating feedback as appropriate into models and metrics.
• Provide timely and accurate response to business, management and regulators. Participate in discussions with model validation, internal and external audits and regulatory reviews

Qualifications:

• Masters (PhD preferred) in a quantitative discipline such as statistics, economics, math, or other sciences.
• Operational risk experience is helpful but not required.
• 1-3 years of financial industry experience.
• An interest and ability to learn the business, regulatory and risk management context
• Extensive experience with statistical analysis, modelling techniques and numerical implementations.
• Programming skills are required. Matlab, SAS, and R are helpful but prior experience in them is not required.
• Experience in developing and maintaining clear documentation for models, model validation, project plans and processes.
• Excellent written and verbal communication skills and the ability to discuss technical issues with clients, peers, auditors, regulators and senior management.

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