Manager, Credit Risk Model Validation

This position requires a seasoned professional as a Senior Manager with specialized knowledge of credit risk management. You will be overseeing the development, enhancement, and validation of credit risk models, ensuring compliance with regulatory standards, and driving innovation in risk management practices. The ideal candidate should have hands-on experience in Credit Risk Model Validation or Development with SAS and Python. You should also possess good hands-on experience in Regulatory Models such as AIRB, CECL, CCAR, Basel, IFRS9. You will primarily work as a consultant for the centralized advanced analytics team of a banking or financial firm focusing on Credit Risk Model Development/Validation and Researcher Specialist. Your responsibilities will include interacting with various business units including risk, finance, controllership stakeholders, and coordinating with auditors and model development or validation teams to ensure adherence to Enterprise Modeling Governance standards. Your activities will involve providing thought leadership, developing and executing modeling strategies, designing, developing, and validating predictive models, conducting testing and validation methodologies, providing analytical support for risk mitigation, assessing data quality, leading and mentoring junior team members, proposing monitoring system improvements, conducting in-depth research on credit risk modeling policies, and contributing to white-paper creation. Minimum Qualifications: - Experience in developing, validating models and risk management of credit risk models. - Knowledge of various statistical techniques and proven skill in regulatory and non-regulatory credit risk modeling. - Understanding and experience with regulatory risk model development/validation guidelines such as SR 11-7, Basel IRB, CCAR, CECL, IFRS9, etc. - End-to-end development or independent validation of credit risk and regulatory models (PD, LGD, EAD, Stress Testing, CECL, Credit Scorecards, AML, counter fraud models, etc.). - Expertise in developing statistical/mathematical and machine learning based models, working with large data sets using SQL, ETL, SAS, Python, R. - Master's degree in a quantitative discipline (Statistics/Economics/Finance/Data Science, etc.). - Strong client management, communication, presentation skills. - Self-driven, proactive, with a "can-do" attitude, able to work under ambiguity and minimal supervision. - Strong project management experience, ability to communicate and coordinate across multiple business units. - Lead projects, provide thought leadership, technical guidance, training, and oversight. Preferred Qualifications: - Strong networking, negotiation, influencing skills. - Knowledge of credit risk management for retail and wholesale lending products. - Hands-on experience in Machine Learning modeling techniques. - Prior Project Management and People Management expertise. Required Skills And Certifications: - Model Validation. - SAS. - Python. - Regulatory Model. - Model Development. - Credit Risk.,