Credit Risk Manager

iBusiness Funding•Fort Lauderdale, FL

About The Position

The Credit Risk Manager develops, implements, and monitors data-driven credit strategies that support iBusiness Funding’s lending growth while maintaining credit performance within parameters established by the Risk team. The role analyzes origination, pipeline, and portfolio data to improve application intake, approval quality, and funding pull-through while evaluating risk-adjusted returns. The position owns and enhances business intelligence reporting for pipeline and credit performance, including dashboards built in Amazon QuickSight and other BI tools. In collaboration with Credit Risk, Modeling, Analytics, Product, Operations, and Technology, the Credit Risk Manager turns insights into credit policy, decision rules, model implementation, and ongoing monitoring. The role also works directly with embedded lending partners to implement partner-specific credit models, supports investors and warehouse lenders with credit performance reporting, and contributes to launching new lending products and channels. Success requires strong analytical and technical capabilities, sound credit judgment, and a commercial approach to profitable growth.

Requirements

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

Nice To Haves

Experience with small business or commercial credit, embedded finance, partner-originated lending, or multi-lender platforms.
Proficiency with BI tools, Python, SQL, and advanced Excel; familiarity with R or other analytical tools is a plus.
Experience supporting credit model development, independent validation activities, production implementation, and ongoing monitoring.
Experience preparing portfolio credit performance reporting for institutional investors, warehouse lenders, or other capital providers.
Demonstrated success improving origination conversion and funded volume while maintaining stable credit performance and attractive risk-adjusted returns.

Responsibilities

Develop and refine credit strategies using application, offer, funding, and portfolio performance data to optimize growth within approved risk appetite and credit performance targets.
Identify opportunities to improve application intake, approvals, offer acceptance, closing, and funded-loan pull-through by segment, channel, product, and lending partner.
Assess risk versus return, including expected credit losses, delinquency, defaults, pricing, profitability, and portfolio yield; recommend credit policy and decisioning changes.
Conduct cohort, vintage, funnel, segmentation, and scenario analyses to test strategies, quantify tradeoffs, and measure implementation results.
Build, update, and maintain Amazon QuickSight dashboards and other BI reporting for pipeline oversight, credit monitoring, executive decisions, and operating reviews.
Track applications, approvals, declines, offers, closings, fundings, and credit outcomes by loan size, product, channel, partner, model, and credit segment.
Monitor credit quality, vintage performance, delinquency, charge-offs, loss rates, and emerging risk indicators; investigate adverse movements and recommend corrective actions.
Work with Data, Analytics, and Technology teams to improve data integrity, reporting definitions, dashboard automation, and access to risk insights.
Support the Modeling team in credit model development, validation, testing, rollout, and post-implementation performance monitoring from a credit strategy perspective.
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.
Collaborate with embedded lending partners to establish and implement partner-specific credit models and decision strategies aligned with program objectives and approved risk thresholds.
Coordinate partner data requirements, model integration, testing, credit policy alignment, performance reporting, and launch readiness with internal and external teams.
Monitor partner-level credit outcomes, conversion, concentrations, and risk-adjusted economics; recommend strategy refinements as performance and volume evolve.
Provide investors and warehouse lenders with credit performance analysis, portfolio trends, model performance, loss and vintage reporting, and responses to risk-related inquiries.
Work with Capital Markets and Finance on portfolio eligibility, risk concentrations, performance discussions, due diligence, and ongoing credit reporting requirements.
Explain credit strategy, policy changes, underwriting performance, and risk mitigation efforts to internal leadership and external funding partners.
Support the design, testing, and rollout of new credit products, lending channels, partner programs, and growth initiatives with appropriate performance guardrails and monitoring.
Partner across Origination, Underwriting, Operations, Product, Risk, Compliance, and Technology to turn credit recommendations into policies, workflows, and decisioning logic.
Document credit strategy decisions, testing, approvals, and performance; escalate material trends and help ensure adherence to Risk team parameters and applicable lending requirements.