Credit Strategy Manager

Job Title: Risk Management-Reporting & Analytics Job Location: SF Bay Area Work Mode: Hybrid (2-3 days/week in office) Compensation Range: $130K - $150K/Yr Base plus Variable Bonus The posted range is the hiring range for this role a subset of the broader range available to employees over time and reflects base salary across our national hiring scale. Final offers are based on several factors, including the candidate's skills and experience, internal pay equity, work location, market conditions for the role, and the specific scope and responsibilities of the position. The top of the range is reserved for candidates who notably exceed the requirements; the lower end applies to those with less experience or fewer preferred qualifications. For positions based in higher-cost zones (e.g., California, New York, New Jersey), actual compensation may exceed the posted range; your recruiter will share specifics during the process. Responsibilities Support financial risk and fraud aspects of business initiatives, including responding to high-severity and time-sensitive risk incidents Apply industry knowledge, statistical modeling, and analytics to develop practical risk strategies using large-scale transactional and account-level data Own the full lifecycle of risk strategy and policy development: identify opportunities, define action plans, test policies, deploy to production, and monitor performance Build expertise across risk types in money movement products, balancing risk mitigation with business growth objectives Partner with Data Science, Risk Operations, Product, Data Engineering, and Analytics teams to design segmentation strategies and portfolio analyses Develop and implement underwriting strategies, including limits, eligibility criteria, and segmentation frameworks Monitor portfolio trends, including concentration risks and segment-level performance Underwriting, credit limits, and eligibility-based decisioning Portfolio monitoring, including segmentation, trend analysis, and concentration risk assessment Financial loss forecasting and behavioral modeling using payments, card/ACH, and account-level data Hypothesis-driven analysis to improve risk strategies and customer outcomes End-to-end policy lifecycle management: design ? test ? launch ? monitor ? iterate Qualifications Strong experience in risk strategy, credit policy, underwriting, fraud or financial analytics Hands-on experience with large datasets and analytical problem-solving Proficiency in SQL and Python for data analysis and model implementation Experience in statistical modeling, forecasting, or risk analytics Ability to translate business problems into data-driven solutions Strong communication and stakeholder management skills Experience working in cross-functional, fast-paced environments Bachelor's degree in quantitative fields such as Data Science, Statistics, Mathematics, Economics, Finance, or Engineering Master's degree in a related quantitative discipline is a plus Experience in financial services, fintech, or risk management domains #J-18808-Ljbffr