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Prosper Marketplace, a leading fintech company and the first peer-to-peer lending platform in the US, is seeking a Director of Collections Strategy & Analytics to lead a high-impact function at the intersection of advanced analytics, AI/ML, and collections strategy.
In this role, you will direct a team leveraging modern Business Intelligence tools, advanced analytics, and machine learning to drive actionable insights across the collections portfolio. You will own the development, validation, and maintenance of loss forecasting models, continuously benchmarking methodologies against industry best practices. You'll champion a rigorous testing culture by designing and executing A/B and multivariate strategy experiments, and monitor portfolio performance at deep segment levels to identify emerging risk trends and performance drivers.
Strategically, you will architect and deploy integrated customer contact and treatment strategies for both early-stage collections and late-stage recoveries, bringing innovative approaches to borrower engagement and digital outreach that balance recovery performance with customer empathy. You'll establish robust KPIs and operational dashboards to measure strategic efficiency and financial returns, and synthesize complex analytical findings into clear strategic narratives for executive leadership and external partners.
You will partner cross-functionally with Credit Risk, Marketing, Product, Engineering, and Operations to seamlessly deploy strategies and drive organizational alignment. This is a hybrid role (2 days/week in the SF office) offering the flexibility to work remotely while maintaining high-touch collaboration.
REQUIREMENTS:
- Master's degree in Statistics, Economics, Mathematics, Engineering, Data Science, Business, or related quantitative field
- 10+ years of progressive experience leading advanced analytics and modeling teams in financial services, with direct expertise in consumer lending collections or credit risk management
- Proven track record of building high-performing analytical teams and influencing cross-functional stakeholders; excellent communication and organizational skills
- Deep expertise in statistical modeling, segmentation, loss forecasting, and modern analytics workflows
- Hands-on fluency with SQL, Python/R, and BI/visualization platforms (e.g., Tableau, PowerBI, Looker)
- Exceptional ability to synthesize complex data, prioritize high-impact initiatives, and operate with urgency in a fast-paced environment
- Preferred: Hands-on experience building or deploying predictive machine learning models (e.g., propensity to pay, roll-rate models, channel response models)
