SVP, Model Operations & Analytics Leader at Synchrony overseeing model development lifecycle. Leading multidisciplinary team and enhancing model quality and consistency aligned with governance standards.
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.
Oversee development and implementation of standardized operational frameworks, tools, and documentation practices to improve model quality, consistency, and compliance.
Oversee the development of internal tools and acquisition of software for model development and model 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).
Partner with Model Development CoE and model owners to ensure timely support for model build, refresh, implementation, and ongoing performance 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 and scalability of model development and monitoring.
Act as a thought partner to executive stakeholders by delivering actionable insights and recommendations on model portfolio performance and operational health.
Requirements
Bachelor’s degree in a quantitative or technical discipline (e.g., Data Science, Computer Science, Engineering, Statistics, Operations Research); or high school diploma/GED and 14+ years of data analytics leadership experience in financial services, banking, technology, and/or retail industries.
10+ years of relevant experience in model operations, data engineering, analytics, or model risk governance.
5 years in a senior leadership role managing multidisciplinary teams.
Proven track record in building and leading teams in high compliance, regulated environments.
Deep understanding of the full model development lifecycle, from data readiness and integration to post-implementation monitoring and performance analytics.
Strong experience designing, implementing, and scaling operational frameworks, monitoring systems, and automation tools to enhance model quality and efficiency.
Proficiency in developing business requirements for enterprise data warehouses and model enablement tools; experience with model documentation standards and governance protocols.
Technical expertise in data pipeline development, data testing, and statistical performance monitoring using tools such as Python, SQL, R, and/or commercial analytics platforms.
Demonstrated ability to lead root cause diagnostics and continuous improvement initiatives to reduce model development cycle time and improve scalability.
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