Director, Collections Strategy & Analytics

Prosper•San Francisco Bay Area, CA

4d•Hybrid

About The Position

Prosper is seeking a strategic leader to head the Analytics function within its Collections & Recoveries organization. Reporting to the VP of Collections & Recoveries, the Director will lead analytical teams and optimize portfolio credit performance across the Personal Loans and Credit Card businesses. The role uses modern data stacks, machine learning, and behavioral segmentation to improve collection effectiveness, operational efficiency, and customer experience. The Director oversees AI/ML and business intelligence capabilities, loss forecasting, experimental design, portfolio analytics, and KPI governance. The role also architects and refines customer contact and treatment strategies across early-stage collections and late-stage recoveries, and communicates analytical findings and portfolio performance to executives and external partners. The position works closely with Credit Risk, Marketing, Product, Engineering, and Operations to deploy strategies. This is a hybrid role with two days per week in Prosper’s San Francisco office. The 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 or more years of progressive experience leading advanced analytics and modeling teams in financial services.
Direct expertise in consumer lending collections or credit risk management.
Demonstrated ability to build high-performing analytical teams and influence cross-functional stakeholders.
Strong 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, Power BI, or Looker.
Ability to synthesize complex data, prioritize high-impact initiatives, and work 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’s use of business intelligence tools, advanced analytics, and machine learning to generate 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 experiments to optimize strategies.
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 borrower engagement, digital outreach, and treatment optimization approaches that balance recovery performance with customer empathy.
Present portfolio health, strategy performance, and key metrics to executive leadership and external partners.
Partner with Credit Risk, Marketing, Product, Engineering, and Operations to deploy strategies.
Build and lead high-performing analytics teams and influence cross-functional stakeholders.