Engagement Manager - Credit Risk Strategy

Role: Engagement Manager - Credit Risk Strategy

Location: Bay Area

Type: Hybrid (2-3 days from office)

Roles & Responsibilities

As a Senior Risk Strategy Leader, you will lead the design and execution of enterprise-scale, data-driven financial risk and fraud strategies across money movement products. You will own strategic risk policy direction and oversee the end-to-end policy lifecycle — from opportunity identification and hypothesis development to testing, deployment, monitoring, and optimization — leveraging large-scale data to balance risk mitigation, customer experience, and sustainable business growth. You will serve as a strategic partner to senior leadership and collaborate cross-functionally to drive scalable risk solutions and respond to critical business and risk events.

• Lead the development and execution of financial risk and fraud strategies supporting key business initiatives and rapidly evolving risk environments
• Provide strategic oversight during high-severity and time-sensitive risk incidents, driving coordinated response and mitigation actions
• Leverage advanced analytics, statistical modelling, and deep domain expertise to design scalable risk frameworks using large-scale transactional and account-level data
• Own and optimize the end-to-end risk strategy and policy lifecycle: opportunity identification, strategy design, experimentation, deployment, governance, monitoring, and continuous improvement
• Drive portfolio-level risk management strategies across underwriting, fraud, credit, and money movement products while balancing risk, growth, and customer experience objectives
• Partner with senior stakeholders across Data Science, Risk Operations, Product, Engineering,
• Finance, Compliance, and Analytics teams to influence strategic decisions and business outcomes
• Lead segmentation strategy development, portfolio analytics, and performance deep dives to identify emerging risks and growth opportunities
• Design and refine underwriting frameworks, credit limits, eligibility policies, and customer risk segmentation strategies
• Establish scalable monitoring frameworks and governance processes to proactively manage portfolio trends, concentration risks, and segment-level performance
• Drive hypothesis-led innovation and experimentation to improve approval rates, reduce losses, and enhance operational efficiency
• Mentor and guide junior analysts and strategy team members, fostering analytical excellence and strategic thinking across the organization
• Communicate complex analytical insights and strategic recommendations effectively to executive leadership and cross-functional stakeholders

Key Business Problems / Use Cases:

• Enterprise-scale underwriting, credit policy, and eligibility strategy optimization
• Portfolio risk management, concentration risk assessment, and performance monitoring across customer segments
• Fraud strategy design and money movement risk mitigation across payment ecosystems
• Financial loss forecasting, behavioural modelling, and risk-adjusted growth optimization using payments, card/ACH, and account-level data
• Hypothesis-driven strategy development and experimentation to improve customer outcomes and portfolio profitability
• End-to-end risk policy lifecycle management: strategy design experimentation deployment governance optimization
• Scenario modelling and impact assessment for new products, market expansions, and policy changes
• Cross-functional strategic planning to balance growth, operational efficiency, compliance, and risk exposure
• Extensive experience in risk strategy, credit policy, underwriting, fraud strategy, or financial analytics within financial services or fintech environments
• Proven track record of leading large-scale analytical initiatives and influencing strategic business decisions
• Strong expertise in leveraging large datasets and advanced analytical techniques to solve complex business and risk problems
• Advanced proficiency in SQL and Python for analytics, modelling, and strategy implementation
• Deep experience in statistical modelling, forecasting, risk analytics, and experimental design
• Strong business acumen with the ability to translate complex analytical insights into actionable strategic recommendations
• Excellent executive communication, stakeholder management, and cross-functional leadership skills
• Experience operating in fast-paced, high-growth, and highly regulated environments
• Demonstrated ability to mentor teams, drive collaboration, and influence senior leadership

Candidate Profile:

Preferred Qualifications:

• Bachelor's degree in quantitative fields such as Data Science, Statistics, Mathematics, Economics, Finance, or Engineering
• Master's degree or MBA in a quantitative or business discipline preferred
• Experience in financial services, fintech, banking, payments, or risk management domains
• Exposure to money movement products, payment ecosystems, fraud operations, or lending platforms
• Experience building scalable risk frameworks, governance models, and automated decisioning systems
• Familiarity with modern data platforms, BI tools, and large-scale experimentation frameworks