VP of Credit Risk

Lending P&L & Credit Strategy

• Serve as the GM for lending profitability: own the credit loss rate, approval rate, checkout conversion, unit economics, and yield across our loan portfolio
• Design and optimize the hard-cut / policy layer that sits alongside the score — knockout rules, eligibility criteria, and approval thresholds — using swap-set and champion/challenger analysis to tune the approve/decline boundary against approval-rate and loss targets.
• Define and continuously improve our underwriting criteria — credit policy, model inputs, decisioning logic — to optimize risk-adjusted returns
• Lead collections strategy, including segmentation, treatment paths, agency relationships, and recovery optimization
• Responsibly expand the approvable population into near-prime (and potentially subprime) by integrating and operationalizing alternative data: cash-flow / bank-transaction data, alternative bureau attributes, income and employment verification, and other non-traditional signals.
• Own portfolio performance management: loss forecasting, vintage and roll-rate analysis, early-warning indicators, and inputs to loss reserves.
• Monitor portfolio performance and drive rapid iteration when trends shift

Product Partnership

• Partner closely with the SVP of Product to define improvements to our lending application and borrower-facing iOS and Android apps
• Bring a data-driven and risk-aware lens to product decisions: approval flows, offer presentation, repayment UX, and borrower communications
• Ensure compliance and regulatory considerations are built in from the start, not bolted on
• Build a rigorous test-and-learn engine (champion/challenger, controlled holdouts, A/B) so credit policy decisions are driven by evidence rather than intuition.

Team Leadership

• Lead and develop a lean but high-performing credit risk team, with expected growth as the business continues to scale
• Develop your team's craft and careers while maintaining high standards for output quality
• Champion a culture of rigor and intellectual honesty (getting it right vs. being right) in how the company uses data

AI & Operational Efficiency

• Identify and implement AI-powered tools and workflows to make the Credit Risk & Analytics function more efficient and scalable
• Evaluate and deploy best-in-class tooling for credit modeling, collections automation, data processing, and analytics delivery
• Stay current on the evolving landscape of fintech AI applications and bring relevant innovations to the team