Data Scientist leveraging expertise in chemical engineering and data science to optimize LANXESS production processes. Focused on machine learning, data pipelines, and production optimization.
About the role
- 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.
Benefits
- Annual Incentive Plan target of 25% of salary
- Annual Equity target of 25% of salary
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