Chief Risk Officer
Specialty Capital
We're hiring a Chief Risk Officer to build and lead the analytics function that powers credit decisioning, fraud detection, pricing, and collections strategy across our MCA and factoring portfolios. This is a hands-on leadership role reporting directly to the CEO and Chief Data Science head, ideal for someone who has led model-building teams inside a consumer or small-business lending platform and wants to build that capability from the ground up in a fast-growing, entrepreneurial shop.
What You'll Own
- Design, build, and continuously refine proprietary underwriting and credit risk models for MCA and factoring deals, using LOS data, bank statement/cash flow data, and bureau/third-party data sources
- Build fraud detection and application-quality scoring to reduce first-payment defaults and stacking risk
- Develop pricing and offer-optimization models (factor rate, term, holdback) calibrated to risk-adjusted return targets
- Build vintage/cohort performance monitoring and early-warning indicators across ISO channels, SIC codes, and deal structures
- Partner with underwriting and credit leadership to translate model output into actionable decisioning rules
- Own collections and recovery analytics segmentation, treatment strategy, and roll-rate forecasting
- Build out the data science function, hire, mentor, and set technical standards as the team grows
What We're Looking For
- 7+ years in data science/analytics leadership within consumer or small-business lending, MCA, factoring, or a related specialty finance vertical
- Track record building proprietary credit, fraud, or acquisition models at scale (e.g., experience at a platform lender such as Enova, Shopify, Block, Consumer Lenders, Embedded Financing Companies, Kabbage, or an MCA/alt-lending competitor is a strong plus)
- Deep hands-on skill in Python, SQL, and applied statistical/ML methods (logistic regression, gradient boosting, survival/vintage analysis)
- Experience with cash flow underwriting and bank statement data (Plaid, Ocrolus, or similar aggregators) a plus
- Comfort working with messy, real-world portfolio data and translating it into clear, decision-ready output
- Strong communication skills; able to present model logic and portfolio risk clearly to non-technical executives and capital partners
- Bachelor's or advanced degree in a quantitative field (statistics, mathematics, computer science, computational finance, or related)
- Prior experience building a data science function from scratch, or as an early/founding analytics hire, strongly preferred
- Direct line to the CEO and executive team this role shapes company-wide credit strategy, not just a single product line
Vacancy posted 2 days ago
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