PPNR- Model validationModel development

Overview:

Key Responsibilities:

• Develop and implement statistical models to forecast PPNR components such as net interest income fee income and operating expenses.
• Evaluate model performance and assess the appropriateness of model assumptions inputs and methodologies.
• Conduct thorough validation of PPNR models in accordance with regulatory requirements and best practices.
• Collaborate with stakeholders to understand business needs and ensure model outputs align with organizational objectives.
• Provide expertise and guidance on model development validation and documentation to crossfunctional teams.
• Perform quantitative analysis to identify trends patterns and potential risks in PPNR data.
• Contribute to the enhancement of model governance frameworks policies and procedures.
• Support model implementation and ongoing monitoring activities including model performance tracking and reporting.
• Stay abreast of industry trends regulatory developments and emerging techniques in PPNR modeling and validation.
• Participate in model risk committees and communicate validation findings to senior management.

Required Qualifications:

• Masters or Ph.D. in Statistics Mathematics Economics Finance or a related quantitative field.
• 3 years of experience in quantitative modeling statistical analysis and/or financial risk assessment within the banking or financial services industry.
• Demonstrated proficiency in programming languages such as R Python or SAS for model development and validation.
• Strong understanding of financial products PPNR drivers and balance sheet dynamics.
• Familiarity with regulatory requirements related to model risk management and validation (e.g. SR 117 CCAR DFAST).
• Proven ability to apply advanced statistical and econometric techniques to solve complex business problems.
• Experience with model validation techniques including backtesting stress testing and sensitivity analysis.
• Excellent written and verbal communication skills with the ability to articulate technical concepts to nontechnical stakeholders.
• Detailoriented approach with a focus on accuracy and quality in model development and validation processes.
• Ability to work effectively in a collaborative crossfunctional environment and manage multiple priorities concurrently.

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