Applied AI ML Sr Associate

Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We’re proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions – all while ranking first in customer satisfaction.

The CCB Data & Analytics team responsibly leverages data across Chase to build competitive advantages for the businesses while providing value and protection for customers. The team encompasses a variety of disciplines from data governance and strategy to reporting, data science and machine learning. We have a strong partnership with Technology, which provides cutting edge data and analytics infrastructure. The team powers Chase with insights to create the best customer and business outcomes.

This role sits within CCB Risk Management and is responsible for leading the governance and oversight of vendor fraud models used across the Consumer & Community Banking (CCB) business.

Key responsibilities:

• Manage the end-to-end lifecycle of vendor fraud models, including onboarding, reviews, upgrades, ongoing monitoring, annual assessments, and remediation activities.
• Partner with Product, Risk Strategy, Vendors, Compliance, Legal, and Model Risk Governance & Review (MRGR) teams to support model onboarding and governance.
• Prepare and coordinate model documentation, governance submissions, Fair Lending reviews, and MRGR reviews.
• Monitor model performance, manage Model Risk Issues (MRIs) and action plans, and ensure compliance with governance requirements.
• Evaluate business benefits, risks, and impacts of vendor models and provide actionable insights to senior leadership.
• Lead discussions around model selection, usage rationale, contingency planning, and strategic risk management.

Desired profile:

• Advanced degree (MS or PhD) in a quantitative discipline such as Statistics, Mathematics, Computer Science, Econometrics, Operations Research, or Physics.
• 5+ years of experience in predictive risk modeling and/or model governance within financial services.
• Strong understanding of MRGR, model risk management, Fair Lending reviews, and governance processes.
• Experience in fraud risk modeling and stakeholder management across multiple functions.
• Excellent communication skills and ability to influence senior stakeholders.