VP, Model Operations Product Owner

Job Description:

Role Summary/Purpose:

The VP Model Operations Product Owner will oversee the operational components of the model development lifecycle, including documentation governance, monitoring execution, and support for tooling processes. This role ensures that models are effectively tracked, maintained, and governed post-development, collaborating closely with model developers, validators, and governance teams.

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:

• Define, develop, and own data for firmwide modeling activities and its ongoing monitoring

• Partner with model development teams to define business objectives and pain points, creating feedback loops that inform data and tooling requirements.

• Lead product ownership and business-side management of the evergreen model data store, ensuring alignment with evolving modeling and strategy needs.

• Define, test, and evaluate external and internal datasets in collaboration with model development teams to expand and refine the model data store.

• Identify and translate model monitoring data requirements into technical specifications for integration into the evergreen data store architecture.

• Direct the development or acquisition of internal tools to support model development workflows, including automation pipelines such as AutoML frameworks.

• Drive the design and implementation of tools that support automated monitoring, including alert generation, trend diagnostics, and performance reporting.

• Manage reporting roles and teams, including the Information Architect and Model Operations Product Owner.

• Coordinate cross-functional reporting and tooling initiatives to ensure seamless integration of data infrastructure, automation, and model operations capabilities across teams.

• Communicate progress, risks, and challenges to stakeholders and leadership.

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

Qualifications/Requirements:

• Bachelor’s degree and 7+ years of professional experience in model operations, data engineering, or analytics infrastructure; or in lieu of a Bachelor's Degree, a High School Diploma/ GED and a minimum of 11+ years of professional experience in model operations, data engineering, or analytics infrastructure

• 5+ years in a senior leadership role within a regulated or data-intensive environment.

• Proven experience leading enterprise data architecture or infrastructure initiatives, particularly in support of model development, governance, and performance monitoring.

• Deep understanding of data management principles, including data extraction, transformation, validation, integration, and storage in large-scale environments.

• Demonstrated success in product ownership or business-side stewardship of data platforms, especially enterprise-scale data stores supporting advanced analytics or machine learning use cases.

• Hands-on experience designing and implementing tooling to support model workflows, including AutoML, monitoring automation, pipeline orchestration, and alerting frameworks.

• Strong knowledge of model lifecycle processes, including collaboration with development, validation, and risk teams on data readiness, quality controls, and operational monitoring.

• Familiarity with Model Operations practices and roles (e.g., Model Operations Product Owner, Information Architect) and the ability to effectively manage these functions across an integrated model operations strategy.

Desired Characteristics:

• Bachelor’s degree in a technical or quantitative discipline (e.g., Computer Science, Data Engineering, Statistics, Information Systems, or related field)

• Master’s degree preferred.

• Exceptional verbal and written communication skills demonstrated through executive and cross-functional stakeholder engagement, detailed-oriented documentation, and visual storytelling.

• Advanced critical thinking skills in analytical problem-solving and the ability to use data to break down complex models.

• Strong project management and leadership skills to achieve specific goals within a defined timeline and budget.

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