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Director, Collections Strategy & Analytics

Job in San Francisco, San Francisco County, California, 94199, USA
Listing for: Prosper Marketplace
Full Time position
Listed on 2026-10-20
Job specializations:
  • IT/Tech
    Data Analyst
Salary/Wage Range or Industry Benchmark: 230000 - 287000 USD Yearly USD 230000.00 287000.00 YEAR
Job Description & How to Apply Below
Your Role in Our Mission

At Proper, we are committed to advancing financial well-being through smarter, technology-driven financial solutions. We are seeking an exceptional leader to head our Analytics function within the Collections & Recoveries organization.

As the Director, Collections Strategy & Analytics, you will serve as a strategic leader responsible for optimizing portfolio credit performance across our Personal Loans and Credit Card business lines. Reporting directly to the VP of Collections & Recoveries, you will lead and empower high-performing analytics teams to design, test, and deploy data-driven strategies across the entire credit lifecycle. Leveraging modern data stacks, machine learning, and advanced behavioral segmentation, you will drive collection effectiveness, elevate operational efficiency, and deliver a best-in-class customer experience.

How

you'll make an impact

Advanced Analytics, AI/ML & Loss Forecasting

  • Lead AI/ML & BI Capabilities:
    Direct the team in leveraging modern Business Intelligence tools, advanced analytics, and machine learning techniques to drive actionable insights.
  • Own Loss Forecasting:
    Oversee the development, validation, and maintenance of loss forecasting models. Continuously benchmark and refine forecasting methodologies against industry best practices to maximize accuracy.
  • Experimental Design & Optimization:
    Champion a rigorous testing culture by designing, executing, and evaluating A/B and multivariate strategy experiments.
  • Portfolio Analytics:
    Monitor portfolio performance at a deep segment level to identify emerging risk trends, perform root‑cause analysis, and isolate core performance drivers.
  • KPI Governance:
    Establish robust Key Performance Indicators (KPIs) and operational dashboards to measure strategic efficiency and financial returns.

Strategic Leadership & Innovation

  • Drive End-to-End Strategy:
    Architect, deploy, and refine integrated customer contact and treatment strategies for both early‑stage collections and late‑stage recoveries.
  • Foster Out‑of‑the‑Box Problem Solving:
    Bring innovative approaches to borrower engagement, digital outreach, and treatment optimization that balance recovery performance with customer empathy.
  • Executive & Stakeholder Communication:
    Synthesize complex analytical findings into clear strategic narratives. Regularly present portfolio health, strategy performance, and key metrics to executive leadership and key external partners.
  • Cross‑Functional Synergy:
    Partner with Credit Risk, Marketing, Product, Engineering, and Operations to seamlessly deploy strategies.
Skills that will help you thrive
  • Education:

    Master’s degree in Statistics, Economics, Mathematics, Engineering, Data Science, Business, or a related quantitative field.
  • Experience:

    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.
  • Leadership:
    Proven track record of building high‑performing analytical teams, as well as influencing cross‑functional stakeholders. Excellent communication and organizational skills.
  • Technical & Analytical Expertise:
    Deep expertise in statistical modeling, segmentation, loss forecasting, and modern analytics workflows. Hands‑on fluency with tools such as SQL, Python/R, and BI/visualization platforms (e.g., Tableau, PowerBI, Looker).
  • Agility & Drive:
    Exceptional ability to synthesize complex data, prioritize high‑impact initiatives, and operate with a strong sense of urgency in a fast‑paced environment.
  • Preferred Experience:

    Hands‑on experience building or deploying predictive machine learning models (e.g., propensity to pay, roll‑rate models, channel response models).
Resources to help you prosper
  • A hybrid…
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