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Credit Risk Manager
iBusiness Funding. Develop and refine credit strategies using application, offer, funding, and portfolio performance data .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in credit risk analysis, lending strategy development, and performance monitoring, with a strong focus on data-driven decision-making and collaboration across cross-functional teams. Proficient in utilizing BI tools like Amazon QuickSight for reporting and dashboard creation, alongside a solid understanding of credit scoring and predictive modeling.
Highest-signal resume keywords
Credit Risk AnalysisLending Strategy DevelopmentAmazon QuickSight Dashboard CreationPredictive ModelingData Interpretation
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Credit RiskLending AnalyticsPortfolio ManagementVintage AnalysisCredit ScoringPredictive ModelsModel ValidationData AnalyticsSQLPython
Soft Skills
Analytical Problem-SolvingAttention to DetailWritten CommunicationPresentation SkillsCollaboration
Tools & Technologies
Amazon QuickSightBI PlatformsAdvanced ExcelR
Industry Keywords
Commercial LendingRisk-Adjusted ReturnCredit PerformanceEmbedded FinancePartner-Originated Lending
Tech Stack
Tools & technologiesPythonSQL
About the role
Key responsibilities & impact- Develop and refine credit strategies using application, offer, funding, and portfolio performance data
- Optimize lending growth within approved risk appetite and credit performance targets
- Identify opportunities to improve application intake, approvals, offer acceptance, closing, and funded-loan pull-through
- Assess risk versus return, including expected credit losses, delinquency, defaults, pricing, profitability, and portfolio yield
- Perform cohort, vintage, funnel, segmentation, and scenario analyses
- Build, update, and maintain Amazon QuickSight dashboards and other BI reporting
- Track applications, approvals, declines, offers, closings, fundings, and subsequent credit outcomes
- Monitor credit quality trends, vintage performance, delinquency, charge-offs, loss rates, and emerging risk indicators
- Partner with Data, Analytics, and Technology teams to improve data integrity, reporting definitions, dashboard automation, and risk insights
- Support credit model development, validation, testing, rollout, and post-implementation performance monitoring
- Translate business and credit objectives into model requirements, eligibility criteria, score cutoffs, decision rules, risk tiers, and approval strategies
- Contribute to model validation, back-testing, challenger testing, segmentation reviews, and assessments of model stability and predictive performance
- Establish and implement partner-specific credit models and decision strategies with embedded lending partners
- Coordinate partner data requirements, model integration, testing, credit policy alignment, performance reporting, and launch readiness
- Monitor partner-level credit outcomes, conversion, concentrations, and risk-adjusted economics
- Support investors and warehouse lenders with credit performance analysis, portfolio trends, model performance, loss and vintage reporting, and risk-related inquiries
- Partner with Capital Markets and Finance on portfolio eligibility, risk concentrations, performance discussions, due diligence, and credit reporting
- Support the design, testing, and rollout of new credit products, lending channels, partner programs, and growth initiatives
- Convert credit recommendations into policies, workflows, and decisioning logic with cross-functional teams
- Maintain documentation of credit strategy decisions, testing, approvals, and performance
- Escalate material trends and help ensure adherence to Risk team parameters and applicable lending requirements
Requirements
What you’ll need- Minimum 5 years of experience in credit risk, credit strategy, lending analytics, portfolio management, or a related discipline
- Preferably experience in small business or commercial lending
- Strong knowledge 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 BI platforms
- Ability to interpret large datasets and translate findings into credit action
- Working knowledge of credit scoring and predictive models, model validation and monitoring, score cutoffs, policy rules, and implementation into lending workflows
- Ability to collaborate with Modeling, Data, Technology, Risk, Capital Markets, Operations, and external lending partners
- Strong analytical problem-solving, attention to detail, written communication, and ability to present technical insights to business stakeholders
- Bachelor's degree in Finance, Economics, Statistics, Mathematics, Data Analytics, Business, or a related field, or equivalent relevant experience
- Optional: experience with small business or commercial credit, embedded finance, partner-originated lending, or multi-lender platforms
- Optional: proficiency with BI tools, Python, SQL, and advanced Excel; familiarity with R or other analytical tools a plus
- Optional: experience supporting credit model development, independent validation activities, production implementation, and ongoing monitoring
- Optional: experience preparing portfolio credit performance reporting for institutional investors, warehouse lenders, or other capital providers
- Optional: demonstrated success improving origination conversion and funded volume while maintaining stable credit performance and attractive risk-adjusted returns
Benefits
Comp & perks- Remote work arrangement
- Full-time employment