SVP, Customer Facing Model Development

Job Description:

The SVP, Customer Facing Model Development, will lead the development, deployment, and governance of credit and fraud scoring/decisioning models and manage strategic frameworks across customer-facing model types. This leader will own the end-to-end integration of credit and fraud customer-facing models with operational strategies, business expansion, and product generation. The leader will also ensure compliance with model risk governance, model performance monitoring, and monitoring against financial and risk objectives.

The role will bring expertise in mapping business requirements to model design, application of regression, artificial intelligence, and machine learning methodologies (broadly, AI/ML), utilization of Monte Carlo, bootstrapping, Bayesian techniques, strategic decision making, and regulatory engagement to influence enterprise practices, lead cross-functional initiatives, and drive data-driven outcomes. Additionally this role will require someone who can drive innovation in cloud-based modeling infrastructures, model lifecycle automation, and the application of AI and technology to enhance and accelerate model development.

We’re proud to offer you choice and flexibility. At Synchrony, our way of working allows you to have the option to work from home near one of our Hubs or to come into one of our offices. Occasionally you may be required to commute to a hub or an office for in-person engagement activities such as business or team meetings, training and culture events.

• Lead development of credit and fraud decisioning models for acquisition, account management, and adoption in partner strategies, leveraging deep knowledge of credit use cases to prioritize modeling efforts and manage the model inventory in alignment with business objectives.
• Understand and map credit journeys for a variety of retail credit products; understand model approaches to adapt to each journey and apply creative solutions to challenges.
• Oversee all phases of model development, from business requirements, data evaluation, model design, methodology selection to model development, model documentation, model validation, implementation and monitoring.
• Guide teams in exploring and deploying innovative AI/ML modeling techniques, while ensuring transparency and explainability.
• Identify and help design opportunities for optimizing the model lifecycle, including the use of AI/GenAI solutions, code standardization, CI/CD frameworks, cloud-based automation, automation of governance controls, etc.
• Oversee the quality of comprehensive model documentation and ensure adherence to model governance standards.
• Establish standard guidelines for model development documentation analysis and narratives.
• Drive cross-functional collaboration with credit, growth, marketing, fraud, risk and technology teams.
• Support the SVP of Model Development COE in regulatory, audit, and senior management interactions, representing customer-facing model development activities as needed.
• Manage model inventory and change processes; identify opportunities for simplification and reuse.
• Oversee responses to validation, audit, and regulatory inquiries and drive timely issue resolution.
• Manage and mentor a high-performing team, including direct oversight of VPs across key functional areas such as Acquisition, Account Management, TNF (True-Name Fraud), and TF (Transaction Fraud).
• Develop and engage with regulators for periodic exams.
• Perform other duties and/or special projects as assigned.

• Bachelor’s degree in a quantitative or technical discipline (e.g., Statistics, Mathematics, Computer Science, Economics, Engineering); advanced degree (MS, MBA, or PhD) strongly preferred.
• 10+ years of experience in credit risk modeling, machine learning, or related analytics roles within the financial services industry, with at least 5 years in a senior leadership role.
• Proven track record in developing, implementing, and overseeing customer-facing credit models across the customer lifecycle—including acquisition, account management, credit line changes, fraud detection, and collections.
• Experience in identifying opportunities for improvement and innovation across the model lifecycle, including leveraging new technologies, AI, and techniques.
• Demonstrated success leading large-scale model development initiatives across multiple portfolios, business lines, or partner segments.
• Experience in building and managing model inventories, standardizing documentation practices, and driving simplification or model reuse efforts.
• Proficiency in programming and data analysis tools (e.g., Python, R, SAS, SQL) and experience working with large structured and unstructured datasets.
• Proven ability to influence enterprise-wide modeling practices and collaborate with cross-functional stakeholders in credit, marketing, fraud, finance, risk and technology.

• Exceptional verbal and written…