SVP, Model Operations & Analytics Leader

Job Description:

Role Summary/Purpose:

The SVP, Model Operations & Analytics Leader leads a multidisciplinary team supporting the full model development lifecycle, from data readiness to post-implementation monitoring. This role drives the creation of standardized frameworks, tools, and automation — including developing data pipelines, managing enterprise end-to-end data warehouse, performing preventative and detective data analysis and monitoring of systems — to ensure model quality, consistency, and regulatory compliance. Partnering closely with model developers, risk management, and audit functions, the leader ensures operational alignment with governance standards and regulatory expectations.

They oversee strategic initiatives to enhance efficiency, scalability, and performance monitoring, while also managing business risk. As a key thought partner to senior stakeholders, the role delivers insights into model portfolio health and resource needs. Additionally, this leader drives a talent strategy to foster technical expertise and a high-performance within the function.

Our Way of Working

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 come into one of our offices. Occasionally you may be required to commute to our nearest office for in person engagement activities such as business or team meetings, training and culture events.

Essential Responsibilities:

• Provide strategic leadership for the Model Operations & Analytics function, ensuring seamless operational support across the entire model development lifecycle.

• Build and lead a multidisciplinary team—including data product owners, data & performance analysts, program managers, and documentation reviewers—responsible for pre- and post-modeling activities.

• Oversee development and implementation of standardized operational frameworks, tools, and documentation practices to improve model quality, consistency, and compliance.

• Oversees the development of internal tools and acquisition of software for model development and model operations.

• Oversees the development of business requirements for enterprise evergreen data store and tool to enable effective model development and operations.

• Drive coordination between model developers and strategy development teams to ensure readiness of model inputs and downstream integration of model outputs.

• Establish and maintain a robust model monitoring infrastructure, including design of key performance indicators (KPIs), perform root cause diagnostics, and performance reporting.

• Partner with Model Development CoE and model owners to ensure timely and compliant support for model build, refresh, implementation, and ongoing performance evaluation, including data testing, evaluation.

• Collaborate closely with Model Risk Management and Internal Audit to ensure all model operations align with regulatory and governance expectations.

• Define and lead execution of strategic initiatives to enhance operational efficiency, reduce model development cycle time, and improve scalability of model development and monitoring.

• Represent Model Operations & Analytics leadership in cross-functional forums to provide visibility into performance, resource needs, and strategic priorities.

• Develop and lead talent strategy for the function, cultivating technical and operational expertise, enhancing capability maturity, and fostering a high-performance culture.

• Act as a thought partner to executive stakeholders by delivering actionable insights and recommendations on model portfolio performance and operational health.

• Participate in forums related to strategy monitoring, providing input and visibility into model operations implications and dependencies.

• Partners with strategy owners to lead and represent MO&A in regulatory discussions and examinations.

• Own and manage governance processes and procedures for strategy monitoring and model monitoring, and related operational controls to ensure compliance and consistency across the model lifecycle.

• Perform other duties and/or special projects as assigned.

Qualifications/Requirements:

• Bachelor’s degree in a quantitative or technical discipline (e.g., Data Science, Computer Science, Engineering, Statistics, Operations Research); or in lieu of degree, high school diploma/GED and 14+ years of data analytics leadership experience in financial services, banking, technology, and/or retail industries.

• 10+ y