Senior Vice President, Credit Risk

Responsibilities

• Models and Credit Policy - Leverage bureau, alternative, and internal data to build and evolve machine learning–based underwriting models, including feature engineering, validation, and performance monitoring. Define and manage scalable credit risk policies that adapt to macroeconomic trends and support resilient growth across segments and partnerships.
• Marketing & Targeting - Lead credit-informed targeting across Direct Mail and digital channels, developing response models, pre-approval criteria, and campaign test-and-learn strategies. Optimize targeting efficiency and cost by refining segmentation and expanding acquisition efforts through co-brand and marketplace partnerships.
• Pricing & Product Optimization - Design credit product constructs—including pricing, lines, fees, and rewards—that maximize risk-adjusted return and customer acquisition efficiency. Balance offers and incentives to drive spend and revolve behavior while maintaining long-term portfolio profitability.
• Portfolio Management - Develop dynamic credit line and usage strategies that balance growth and risk, including line increases, spend incentives, and introductory offers. Monitor and optimize portfolio KPIs through cohort analysis, behavioral modeling, and segmentation-led interventions that drive sustained margin performance.
• Fraud and Collections - Manage manage both first- and third-party fraud defenses to protect portfolio health and capital efficiency. Institute sophisticated contact and collections strategies that are both compliant and efficient, leveraging best in breed tools.
• P&L Valuations - Develop and own multi-year credit card P&L and balance sheet models with granular, vintage-based assumptions across revenue, loss, and funding drivers. Apply deep financial modeling expertise to forecast capital needs, inform strategic decisions, and ensure sustainable, long-term portfolio profitability.
• People Leadership - Recruit and develop top-tier credit and risk talent, building a high-performing organization from the ground up. Foster leadership growth, drive organizational change, and ensure the team adapts to evolving market, regulatory, and technology dynamics.

Skills and Attributes

• A blend of strategic vision and operational rigor: equally comfortable crafting high-level credit strategy and rolling up their sleeves to solve detailed credit challenges and lead execution end-to-end.
• Extensive experience building and managing ML-based credit risk models, with deep understanding of model governance, policy development, and performance management across different economic cycles.
• A comprehensive grasp of the U.S. credit card ecosystem, including market dynamics, vintage-based economics, bureau and alternative data, macro trends, regulatory landscape (FCRA, ECOA, UDAAP), and risk methodologies.
• Strong command of financial modeling and portfolio forecasting, with the ability to translate complex data into actionable insights that drive sustainable profitability and informed credit decisions.
• Hands-on familiarity with credit risk infrastructure, from origination and decisioning platforms to fraud detection, collections systems, and external vendor ecosystems.
• Demonstrated ability to build and scale high-performing credit teams, lead cross-functional collaboration across Finance, Legal, Operations, and Tech, and foster a culture of innovation grounded in data, testing, and continuous improvement.

Experience and Qualifications

• At least 15 years of leadership across Credit Risk, Underwriting, Acquisitions, Portfolio Management, and Horizontal Risk (Collections, Fraud) within large U.S. credit card portfolios, including both General Purpose and Co-Brand programs.
• Demonstrated ability to lead data science teams in developing, validating, and deploying ML-based credit risk models, with hands-on collaboration across tech and operations to bring strategies into production.
• Direct experience interfacing with regulators such as the OCC, CFPB, and FRB, with a strong track record of managing regulatory exams, audits, and implementing robust compliance governance frameworks.
• Prior success in launching or scaling new credit programs—ideally in a fintech or fast-moving environment that demands rapid experimentation, risk-reward tradeoffs, and decision velocity.
• An advanced degree in Engineering, Economics, Finance, Statistics, Mathematics, or a related quantitative field is preferred.