Sr. Director of Credit Risk Analytics

The Sr. Director of Credit Risk Analytics is a senior leadership role responsible for the full Credit Policy function — from strategy design through execution and measurement. You will own the credit program's analytical infrastructure, set the team's agenda, and be the primary accountable owner for portfolio profitability. This is a high-visibility role that requires equal parts strategic vision and quantitative rigor, with a strong bias toward structured experimentation and evidence-based decision-making. 

You will report directly to the Chief Risk Officer and serve as a key cross-functional partner to the Data Science, Finance, Product/Tech, and Sales teams. 

• Define and own the Credit Policy roadmap, setting the team's agenda in alignment with company growth, risk appetite, and profitability objectives
• Determine which underwriting strategies, credit policy levers, and product term configurations to pursue — and in what sequence
• Partner with the Data Science team to translate policy intent into model inputs, scorecard strategies, and decisioning logic
• Ensure that credit policy decisions account for second-order effects, including merchant engagement and performance impacts associated with changes 

• Design, execute, and monitor controlled experiments (A/B tests, champion/challenger frameworks) for all material credit policy and product term changes prior to full rollout
• Establish rigorous experimental design standards that ensure clean attribution — isolating the impact of individual policy changes from macro, seasonal, and cohort effects
• Define the measurement framework for each test, identifying the appropriate primary and guardrail metrics
• Synthesize test results into clear, defensible recommendations and present findings to senior leadership and cross-functional partners 

• Own ongoing monitoring of portfolio health across a comprehensive suite of KPIs, including delinquency rates, roll rates, early buyout rates, loss curves, and terminal outcomes by cohort, vintage, vertical, and channel
• Build and maintain analytical frameworks that allow the team to quickly surface emerging portfolio trends and distinguish signal from noise
• Identify risk concentrations, underperforming segments, and policy gaps, and drive timely remediation through credit policy adjustments 

• Lead portfolio forecasting using a combination of horizontal and vertical performance metrics to produce reliable point-in-time portfolio performance projections
• Partner with FP&A and Capital Markets to ensure credit forecasts are integrated into financial planning, capital allocation, and investor reporting processes
• Develop scenario analysis and stress-testing capabilities to assess the portfolio's sensitivity to macroeconomic changes, product mix shifts, and channel growth assumptions 

• Design and own a valuations framework and model that enables analysts on the team to rapidly and reliably model the unit economics impact of changes to credit policy, product terms, and origination mix
• Ensure the model is flexible enough to support "what-if" scenario gaming across key levers (e.g., APR equivalents, payment cadence, term length, approval tier thresholds) while maintaining analytical integrity
• Work with Finance and Capital Markets to align valuation assumptions with capital markets pricing, funding cost structures, and investor reporting standards 

• Lead, mentor, and develop a team of four: a Senior Analyst, Manager, Senior Manager, and Director — establishing clear goals, growth paths, and accountability structures
• Foster a culture of intellectual rigor, curiosity, and ownership within the team
• Build scalable analytical processes and documentation standards that reduce key-person dependency and support team growth as the business scales
• Represent the Credit Policy function in cross-functional forums and serve as a thought partner to peer leaders across Risk, Data Science, Product, and Finance 

• Bachelor’s degree required, in a quantitative field such as Statistics, Mathematics, Economics, Business, or Engineering preferred
• 7+ years of experience in an analyst, data science, or consulting role
• 5+ years of experience in credit risk analysis, credit policy, or a closely related function within consumer or small business lending, leasing, or installment finance
• Prior experience with Lease-to-Own, BNPL, installment lending, other non-traditional consumer credit products preferred 
• Deep proficiency in credit performance analytics: delinquency curves, roll rate analysis, loss forecasting, vintage analysis, and cohort-based performance attribution
• Expert-level command of experimental design, including A/B testing, champion/challenger frameworks, and statistical significance testing; a demonstrated ability to isolate causal effects and defend attribution in complex, multi-variable environments
• Strong financial modeling skills including the ability to translate credit performance assumptions into unit economics, portfolio valuations, and P&L impact
• Proficiency in Excel, SQL, and Python; comfort working with large datasets and interfacing with data science and data engineering teams
• Proven ability to lead and develop analytical teams, including managing managers
• Exceptional communication skills — able to translate complex quantitative findings into crisp, actionable narratives for executive and cross-functional audiences
• High degree of intellectual honesty; comfortable challenging assumptions, acknowledging uncertainty, and changing course when data warrants it
• Strong instincts for prioritization in a fast-moving, resource-constrained environment 

• We focus on what’s most important
• We set clear expectations and deliver
• We embrace challenges to reach our full potential
• We ask, “How can this be better?”
• We move fast together