Retail Risk Product Owner

Experienced Retail Risk Product OwnerRequired Education: Bachelor's degree in finance, Economics, Computer Science, Engineering, or a related quantitative field. Preferred Education: Master's degree or MBA preferred.Required Qualifications/Skills/Experience: 10+ years of experience in product management, business analysis, or a similar role within financial services, with a strong focus on retail risk. 5+ years of direct experience with CCAR, DFAST, or similar regulatory stress testing frameworks and loss forecasting processes. Proven track record of successfully delivering complex technology platforms or products in an agile environment. Strong understanding of retail credit products (e.g., credit cards, mortgages) and associated risk drivers. Understanding of risk modeling concepts (PD, LGD, EAD) and complete flows from data to models to regulatory consumption. Knowledge of relevant technologies such as Python, UI/UX, SQL and platforms used in regulatory processes. Deep expertise in retail credit risk, regulatory stress testing (CCAR), and agile product management methodologies. Ability to bridge the gap between Retail and Wealth Risk business needs, risk management requirements, and technical development teams. Experience working closely with agile development teams (scrum masters, developers, QA) throughout the entire product lifecycle. Ability to define the product vision, strategy, roadmap, and features for next-generation risk analytics and forecasting capabilities. Maintain an in-depth understanding of retail credit risk methodologies, CCAR, DFAST, CECL, and other relevant regulatory guidelines (e.g., SR 11-7). Ability to ensure platform design and functionality support robust data governance, model risk management, and auditability for regulatory submissions. Strong stakeholder management and communication skills. Ability to monitor platform performance, user feedback, and regulatory changes to identify areas for continuous improvement and innovation. Champion a data-driven approach to product development, utilizing analytics to inform decisions.Preferred Qualifications/Skills/Experience: Experience using AI assisted tools is a plus.Job Duties: Lead the development and enhancement of a new Loss Forecast Platform for use in CCAR and internal loss forecast processes. Bridge the gap between Retail and Wealth Risk business needs, risk management requirements, and technical development teams. Define the product vision, strategy, roadmap, and features for next-generation risk analytics and forecasting capabilities. Ensure the platform is robust, scalable, and compliant. Define and articulate the product vision, strategy, and roadmap for the Loss Forecast Platform, aligning with overall business objectives and regulatory requirements. Conduct market research, competitive analysis, and gather stakeholder feedback to identify new opportunities and inform product decisions. Translate high-level strategic objectives into detailed product requirements and user stories to bring efficiency to the organization. Act as the primary liaison between risk management, finance, technology, and other key stakeholders to capture, analyze, and prioritize business requirements for CCAR, retail loss forecasting models, and other platform functionalities. Develop and maintain a well-groomed product backlog, ensuring stories are clearly defined, estimated, and prioritized based on business value, regulatory urgency, and technical feasibility. Facilitate workshops and discussions to elicit detailed requirements and resolve ambiguities. Provide clear guidance and answer questions from development teams during sprint cycles to ensure accurate understanding and implementation of features. Participate in all agile ceremonies, including sprint planning, daily stand-ups, sprint reviews, and retrospectives. Oversee user acceptance testing (UAT) to ensure delivered solutions meet specified requirements and quality standards. Maintain an in-depth understanding of retail credit risk methodologies, CCAR, DFAST, CECL, and other relevant regulatory guidelines (e.g., SR 11-7). Ensure the platform design and functionality support robust data governance, model risk management, and auditability for regulatory submissions. Collaborate with model development and validation teams to integrate advanced loss forecasting models into the platform effectively. Effectively communicate product updates, progress, risks, and challenges to senior management and relevant stakeholders. Manage expectations and negotiate scope trade-offs to achieve optimal outcomes. Monitor platform performance, user feedback, and regulatory changes to identify areas for continuous improvement and innovation. Champion a data-driven approach to product development, utilizing analytics to inform decisions.