Director of Data Science

About the Company

ClarityPay is a fast-growing fintech that redefines the point-of-sale credit market. Based in NYC and Atlanta, the company empowers large merchants with configurable "Pay-Over-Time" tools, including monthly installments, BNPL, and revolving products.

Responsibilities

• Own the full lifecycle of Probability of Default (PD) models for installment loan and BNPL originations
• Build and maintain LGD and EAD models to support expected loss calculations and pricing optimization
• Develop vintage-level loss curves and roll-rate frameworks to forecast portfolio performance
• Integrate alternative data sources to improve predictive lift
• Define and maintain decision scorecards and cutoff strategies across product tiers
• Partner with Pricing to ensure PD output feeds into IRR-based pricing frameworks
• Build real-time model serving pipelines in collaboration with Data Engineering
• Establish performance monitoring frameworks including PSI, CSI, and vintage-level deviation tracking
• Hire, mentor, and grow a team of data scientists
• Represent modeling approaches to warehouse lenders and investors during due diligence

Requirements

• 10+ years of experience in quantitative modeling
• 3+ years focused on consumer credit risk
• Deep expertise building PD models using logistic regression, gradient boosting (XGBoost/LightGBM), or survival models
• Strong Python (pandas, scikit-learn, statsmodels) and SQL skills
• Experience with credit bureau data (Experian, Equifax, TransUnion)
• MS or PhD in Statistics, Mathematics, Economics, Computer Science, or a related quantitative field

Preferred Qualifications

• Experience at a fintech lender, BNPL company, or marketplace lender
• Familiarity with CECL / IFRS 9 expected loss frameworks
• Experience presenting model frameworks to institutional investors or during ABS securitization diligence
• Exposure to fair lending testing (disparate impact and adverse action analysis)
• Prior people management or mentorship experience