Credit Risk Manager.

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Credit Risk Manager based in the United States.

This is an opportunity to shape data-driven credit strategies that support sustainable lending growth while maintaining strong portfolio performance. You will analyze origination, application pipeline, and loan portfolio data to improve approval quality, funding conversion, and risk-adjusted returns. The role combines credit judgment, advanced analytics, business intelligence, and cross-functional execution in a technology-enabled lending environment. You will own and enhance reporting capabilities, including dashboards built with Amazon QuickSight, and translate insights into practical credit policies and decisioning strategies. Working with internal teams and external lending partners, you will contribute to model implementation, portfolio monitoring, and the launch of new lending products and channels. This remote, full-time position offers the opportunity to influence lending performance and support the growth of small business and commercial financing programs.

Accountabilities

• Develop and refine data-driven credit strategies that balance lending growth with approved risk appetite and credit performance targets.

• Analyze application intake, approvals, offers, acceptance, closing, and funded-loan conversion to identify improvement opportunities across products, channels, partners, and customer segments.

• Evaluate risk-adjusted returns using expected credit losses, delinquency, defaults, pricing, profitability, and portfolio yield, recommending credit policy and decisioning adjustments as needed.

• Conduct cohort, vintage, funnel, segmentation, and scenario analyses to test strategies, quantify trade-offs, and measure post-implementation results.

• Build, maintain, and improve Amazon QuickSight dashboards and other BI reporting tools to support pipeline oversight, portfolio monitoring, executive decisions, and operational reviews.

• Track application and loan performance metrics, including approvals, declines, fundings, delinquency, charge-offs, loss rates, and emerging risk indicators.

• Collaborate with Data, Analytics, and Technology teams to improve data quality, reporting definitions, dashboard automation, and access to actionable insights.

• Support credit model development, validation, testing, implementation, and ongoing monitoring in collaboration with the Modeling team.

• Translate business objectives and credit requirements into model specifications, eligibility criteria, score cutoffs, decision rules, risk tiers, and approval strategies.

• Work with embedded lending partners to implement partner-specific credit models, coordinate data requirements and testing, align credit policies, and monitor performance.

• Provide investors and warehouse lenders with credit performance analysis, portfolio trends, model results, loss and vintage reporting, and responses to risk-related inquiries.

• Partner with Capital Markets and Finance on portfolio eligibility, risk concentrations, due diligence, and ongoing credit reporting.

• Support the design and rollout of new credit products, lending channels, partner programs, and growth initiatives with appropriate risk controls and monitoring.

• Work across Origination, Underwriting, Operations, Product, Risk, Compliance, and Technology to translate credit recommendations into effective policies, workflows, and decisioning logic.

• Maintain clear documentation of strategy decisions, testing, approvals, and performance, escalating material trends and supporting adherence to risk parameters and applicable lending requirements.

Requirements:

• At least 5 years of experience in credit risk, credit strategy, lending analytics, portfolio management, or a related discipline; experience in small business or commercial lending is preferred.

• Strong understanding of lending funnels, underwriting decisioning, portfolio credit metrics, vintage analysis, loss performance, and risk-adjusted return measurement.

• Hands-on experience developing dashboards and reports using Amazon QuickSight or comparable business intelligence platforms.

• Ability to interpret large datasets and turn analytical findings into practical credit strategies and business recommendations.

• Working knowledge of credit scoring and predictive models, model validation and monitoring, score cutoffs, credit policy rules, and implementation within lending workflows.

• Strong analytical and problem-solving skills, attention to detail, and the ability to communicate complex technical insights clearly to business stakeholders.

• Ability to collaborate effectively with Modeling, Data, Technology, Risk, Capital Markets, Operations, and external lending partners.

• Bachelor's degree in Finance, Economics, Statistics, Mathematics, Data Analytics, Business, or a related field, or equivalent relevant experience.

• Nice to have: Experience in small business or commercial credit, embedded finance, partner-originated lending, or multi-lender platforms.

• Nice to have: Proficiency in BI tools, Python, SQL, and advanced Excel; familiarity with R or other analytical tools is an advantage.

• Nice to have: Experience supporting credit model development, independent validation, production implementation, and ongoing performance monitoring.

• Nice to have: Experience preparing portfolio credit performance reports for institutional investors, warehouse lenders, or other capital providers.

• Nice to have: A track record of improving origination conversion and funded volume while maintaining stable credit performance and attractive risk-adjusted returns.

Benefits:

• Remote work arrangement based in the United States.

• Full-time opportunity within a technology-enabled lending and risk management environment.

• Broad ownership of credit strategy, business intelligence reporting, and portfolio performance initiatives.

• Cross-functional collaboration with teams across Risk, Modeling, Analytics, Product, Technology, Operations, and Capital Markets.

• Exposure to embedded lending partnerships, institutional funding relationships, and the development of new lending products.

• Opportunity to influence measurable improvements in lending conversion, credit performance, and risk-adjusted growth.