Director, Collections Strategy & Analytics

Prosper•San Francisco, CA

8h•$230,000 - $287,000•Hybrid

About The Position

Prosper is seeking a leader to head the Analytics function within its Collections & Recoveries organization. Reporting to the VP of Collections & Recoveries, the Director will optimize portfolio credit performance across the Personal Loans and Credit Card business lines. The role leads analytics teams in designing, testing, and deploying data-driven strategies throughout the credit lifecycle, using modern data stacks, machine learning, and behavioral segmentation to improve collection effectiveness, operational efficiency, and customer experience. The Director oversees analytics, AI/ML, business intelligence, loss forecasting, portfolio performance monitoring, KPI governance, and experimental design. The position also architects and refines customer contact and treatment strategies across early-stage collections and late-stage recoveries, communicates portfolio and strategy results to executives and external partners, and collaborates with Credit Risk, Marketing, Product, Engineering, and Operations. This is a hybrid position requiring two days per week in Prosper’s San Francisco office. The stated annual salary range is $230,000–$287,000, plus bonus and benefits.

Requirements

Master’s degree in Statistics, Economics, Mathematics, Engineering, Data Science, Business, or a 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 or R, and BI or visualization platforms such as Tableau, PowerBI, or Looker.
Ability to synthesize complex data, prioritize high-impact initiatives, and operate with urgency in a fast-paced environment.

Nice To Haves

Hands-on experience building or deploying predictive machine learning models, such as propensity-to-pay, roll-rate, or channel-response models.

Responsibilities

Lead the team in using business intelligence tools, advanced analytics, and machine learning to produce actionable insights.
Oversee the development, validation, and maintenance of loss forecasting models, and benchmark and refine forecasting methodologies.
Design, execute, and evaluate A/B and multivariate strategy experiments.
Monitor portfolio performance at a deep segment level, identify emerging risk trends, conduct root-cause analysis, and isolate performance drivers.
Establish KPIs and operational dashboards to measure strategic efficiency and financial returns.
Architect, deploy, and refine integrated customer contact and treatment strategies for early-stage collections and late-stage recoveries.
Develop innovative approaches to borrower engagement, digital outreach, and treatment optimization while balancing recovery performance with customer empathy.
Present portfolio health, strategy performance, metrics, and analytical findings to executive leadership and external partners.
Partner with Credit Risk, Marketing, Product, Engineering, and Operations to deploy strategies.