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