As a Principal Credit Analytics, you will lead a key pillar of these functions, credit forecasting & valuation or risk capital analytics—driving high-impact analytics that inform portfolio strategy, financial planning, and funding decisions. You’ll partner closely with Machine Learning, Finance, Product, and Capital teams to translate complex credit dynamics into actionable insights and scalable systems.

How you’ll make an impact

• Own a core analytics domain within Credit Analytics (forecasting & valuation or risk capital), driving execution and continuous improvement of frameworks that power portfolio monitoring, planning, and decision-making
• Develop and enhance credit forecasting and valuation methodologies, including loss forecasting, scenario analysis, and portfolio performance measurement, ensuring outputs are accurate, explainable, and decision-useful
• Contribute to risk capital analytics and reporting, supporting funding strategies such as securitizations, warehouse facilities, and forward-flow programs through robust performance tracking, stress scenarios, and risk/return analysis
• Translate analytics into business impact, delivering clear insights and recommendations that guide product strategy, credit policy, and funding decisions
• Partner cross-functionally with ML, Finance, Product, Engineering, and Capital teams to align on definitions, metrics, and frameworks, and to integrate analytics into core workflows and decision processes
• Build and scale analytics infrastructure, including data models, pipelines, dashboards, and reporting tools that enable consistent, self-serve insights across stakeholders
• Uplevel analytical rigor and processes, establishing best practices for validation, monitoring, and governance of credit models and analytics outputs

Minimum Qualifications

• 7+ years of experience in analytics, credit risk, or quantitative finance within fintech, financial services, or related industries
• Experience building or applying credit risk / loss forecasting, portfolio analytics, or valuation frameworks in consumer lending or similar domains
• Exposure to risk capital or structured finance concepts (e.g., securitizations, warehouse facilities, forward flow, or investor reporting)
• Strong analytical and technical skills, including proficiency in SQL and at least one programming language (Python or R), and experience working with large datasets
• Ability to translate complex analyses into clear, actionable insights for both technical and non-technical stakeholders

Preferred Qualifications

• Experience partnering with ML / data science teams, particularly in underwriting or model performance monitoring
• Familiarity with capital analytics, deal economics, and risk/return frameworks
• Experience building or improving analytics infrastructure (data models, dashboards, automated reporting, GenAI solutions)
• Exposure to model governance, controls, or audit processes (e.g., SOX, model validation, valuation reviews)
• Demonstrated ability to influence cross-functional stakeholders and drive alignment across teams

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