Job
Description
Department: Credit Analytics and Innovation model governance team Reports to: Head of Model Validation --- Role Overview: We are seeking an experienced and motivated Senior Analyst – Model Validation at the AVP level to join our Model Risk team. This role offers a unique opportunity to lead and shape the automation and proactive monitoring framework for models across the bank. The ideal candidate will have a deep understanding of model development, strong technical expertise in Python and PySpark, and experience interacting with cross-functional teams including credit risk, data science, model governance, and senior management. --- Key Responsibilities: Lead the automation of model monitoring pipelines, ensuring timely and robust performance tracking across all key models used within the bank. Develop and maintain monitoring tools to proactively identify stress signals or model performance degradation, enabling timely model reviews or rebuilds. Collaborate closely with the enterprise-level model validation unit to ensure full compliance with model governance policies and regulatory expectations. Act as the primary point of contact for the internal credit risk team, model owners, and data science teams for all matters related to monitoring, data submission, and model lifecycle governance. Prepare and deliver clear, insightful presentations to senior management committees on model performance, validation findings, and governance metrics. Participate in or lead discussions with risk management stakeholders and contribute to key decision-making forums. Support model validation reviews by providing insights into model usage, design assumptions, and business impact. Drive process improvements and contribute to the adoption of advanced analytics and automation tools within model governance and monitoring. --- Required Skills and Experience: 5–8 years of experience in model development, validation, or risk analytics in the financial services industry. Strong knowledge of model development lifecycle (ML models, credit, collection and fraud models ). Hands-on expertise in Python and PySpark is essential; experience in model deployment frameworks is a plus. Proven track record of automating analytics or monitoring pipelines using modern data tools and platforms. Familiarity with model governance frameworks, regulatory requirements and documentation best practices. Exceptional communication skills with the ability to interact confidently with senior stakeholders and present complex findings clearly. Strong interpersonal and negotiation skills for managing multiple stakeholders across credit risk, data science, validation, and governance teams. Demonstrated ability to manage priorities in a fast-paced, multi-stakeholder environment. --- Preferred Qualifications: Master’s degree in Quantitative Finance, Statistics, Computer Science, Economics, or related fields. Prior experience in a model risk, model validation, or enterprise risk function in a banking or financial services environment. Exposure to cloud environments (e.g., AWS, Azure) and modern model monitoring platforms is a plus. --- Why Join Us: Be at the forefront of model risk transformation and governance innovation. Work in a highly collaborative environment with visibility across senior management. Contribute to meaningful risk decisions that shape the bank’s strategic direction. Show more Show less
