Manager, Model Risk and Governance

Responsibilities

• Lead, grow, and develop a team of 3+ data scientists and governance professionals.
• Own performance monitoring, drift monitoring, fair lending assessments, governance documentation, validation, model inventory, and change management.
• Set the strategy for model risk and governance, including automation, standardization, and process improvements.
• Own governance-related relationships across Data Science, Engineering, Partner Success, and Sales.
• Manage customer relationships, including customer-facing calls with model risk teams at banks and fintechs.
• Guide customers in advancing adoption while meeting governance standards.
• Prepare validation reports, governance documentation, and performance summaries for leadership, customers, auditors, and regulators.
• Track governance findings through remediation and manage the team roadmap.
• Contribute hands-on when needed to move work forward and mentor the team.

Requirements

• 8+ years of experience in model risk management, model validation, model governance, or quantitative risk.
• 4+ years of people management experience, including building and scaling model risk or governance teams.
• Deep knowledge of model governance for financial institutions, including SR 11-7, SR 26-2, OCC guidance, fair lending, and the regulatory landscape.
• Experience validating or governing machine learning or statistical models in a regulated environment.
• Technical depth sufficient to read models, interrogate methodologies, and collaborate effectively with data scientists.
• Working knowledge of Python and proficiency in SQL.
• Strong analytical skills using Excel or Google Sheets.
• Excellent written and verbal communication skills, including the ability to translate technical findings for technical and non-technical audiences.
• Bachelor's degree in a quantitative field such as Mathematics, Statistics, Computer Science, Engineering, Economics, or a related STEM discipline.
• Legal authorization to work in and residence in the United States.

Nice to Haves

• Experience with fraud, identity verification, credit risk, or financial risk models.
• Experience supporting model governance at banks or other regulated financial institutions.
• Experience with AWS, including S3 and SageMaker.
• Experience with GitHub.
• Master's degree in a quantitative field.

Technologies

• Python 3
• PostgreSQL
• AWS EC2, S3, RDS, and Redshift

Compensation and Benefits

• $210,000-$240,000 per year, plus equity and benefits.
• Employer-paid group health insurance for employees and dependents.
• 401(k) plan with employer match.
• Flexible paid time off.
• Regular company-wide in-person events.
• Home office stipend.