Vice President, Model Risk Management

Description We are seeking a future team member for the role of VICE PRESIDENT to join our MODEL RISK MANAGEMENT team in PUNE . This role supports the independent validation of models used across the firm and may align to one or more of the following areas: 1) Credit Risk Modeling (Wholesale or Retail portfolios), 2) Operational Risk, 3) Capital Stress Testing In this role, you will: - Lead and execute independent model validations in accordance with enterprise model risk management standards for model validation, by setting the scope of a validation effort. - Define the scope, validation approach, and testing strategy for assigned models, including conceptual review, data assessment, methodology evaluation, outcomes analysis, benchmarking, implementation review, and performance monitoring assessment. - Assess the conceptual soundness, assumptions, limitations, and fitness for purpose of models, and identify circumstances under which model performance or usefulness may deteriorate. - Develop clear, well-supported validation conclusions and communicate model strengths, weaknesses, limitations, and risks through high-quality technical documentation and validation reports. - Provide effective challenge to model developers and stakeholders on model design, assumptions, methodology, performance, and model use. - Review analyses, calculations, and documentation prepared by junior team members to ensure technical accuracy, consistency, and adherence to validation standards. - Complete required training, disclosures, attestations, and certifications within deadlines. - Demonstrate curiosity and willingness to embrace emerging AI capabilities to support BNY’s AI-first strategy, including the development and adoption of AI agents and digital employees. To be successful in this role, we are seeking the following: - Master's Degree or PhD in a quantitative discipline, including engineering, mathematics, physics, statistics, econometrics. - 5–7 years of relevant experience in model validation, model development, or quantitative risk management within financial services. - Strong understanding of model risk management principles and applicable regulatory guidance, such as SR 11-7, SR – 26 –2, SR 15-18, CCAR, Basel, CECL, IFRS9, EMIR, PRA SS1/23, etc. - Possess a strong analytical background with a solid theoretical foundation coupled with advanced computational programming, technical documentation, and communications skills. - Experience of working with PD / LGD / EAD models, Wholesale and retail credit risk, Scorecards / rating models, Stress testing / scenario models, Portfolio risk concepts (default, migration, concentration, provisioning, economic capital, RWA). - Must have experience with complex quantitative modelling, numerical analysis, and computational methods using programming languages (such as Python, R, C++, Java, MATLAB, SAS) as well as mathematical/statistical software packages. - Familiarity with AI-enabled tools and digital agents (i.e. BNY's patented AI Agent - Eliza) to enhance analytical workflows, improve productivity, and deliver high-quality outputs. - Ability to effectively partner with AI tools and intelligent Digital Employees to accelerate research, validation, documentation, and insight generation while applying strong professional judgment.