Website Prosper
Money when you need it. Fast, easy, secure.
Location:Â Remote (United States)
Company:Â Prosper
Position:Â Manager, Collections Analytics
Salary:Â $132,000 – $194,000 annually + bonus + comprehensive benefits
Also See: Organization Effectiveness Enablement Lead
Lead Data-Driven Strategy at a Pioneering FinTech Company
Prosper is the first peer-to-peer lending marketplace in the U.S., having originated over $28 billion in loans to advance financial well-being. We are a mission-driven, data-centric company where analytics powers our competitive edge. Join us as a Collections Analytics Manager to lead the strategy that optimizes our collection and recovery operations for personal loans and credit cards. This is a high-impact role where your work directly influences credit performance and customer outcomes.
The Role: Manager, Collections Analytics
As the Manager of Collections Analytics, you will own the data, models, and strategic insights that drive the effectiveness and efficiency of our end-to-end collection activities. You will leverage advanced analytics, machine learning, and statistical modeling to develop, test, and implement strategies that improve recovery rates while balancing customer experience. This is a hands-on leadership role requiring deep analytical expertise, business acumen, and the ability to translate complex data into actionable plans.
Key Responsibilities:
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Provide end-to-end analytical support for collections and recovery, developing strategies to optimize performance across Prosper’s personal loan and credit card portfolios.
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Lead the development and refinement of loss forecasting models, incorporating industry best practices to enhance accuracy and efficiency.
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Conduct granular segmentation analysis, identify key performance drivers, and perform root-cause analysis to explain trends and recommend interventions.
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Partner with Credit Risk, Marketing, Product, and Engineering teams to implement strategies, design A/B tests, and monitor outcomes.
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Continuously test new data sources, analytical approaches, and machine learning techniques to innovate and improve collection strategies.
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Clearly communicate complex analytical findings and strategic recommendations to senior management and cross-functional stakeholders.
Required Skills & Qualifications:
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Bachelor’s degree in Statistics, Mathematics, Computer Science, Economics, Engineering, or a related quantitative field plus 6+ years of relevant analytical experience, OR a Master’s degree plus 4+ years of experience.
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Proven expertise in consumer lending analytics, preferably within collections, recovery, credit risk, or marketing in a FinTech or financial services environment.
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Strong hands-on experience using machine learning and statistical models to develop business strategies.
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Advanced proficiency in SQL is mandatory. Experience with R, Python, Tableau, or Looker is a strong plus.
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Demonstrated ability to lead projects, mentor analysts, and manage stakeholder relationships.
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Excellent problem-solving skills with a curious, innovative mindset that challenges the status quo.
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Outstanding communication skills, with the ability to distill complex technical concepts for broad audiences.
What We Offer:
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$132,000 – $194,000 base salary, plus performance bonus and generous equity.
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Full health coverage, flexible PTO, paid parental leave, 401(k) match, Udemy access, wellness stipends, and more.
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Play a key role in the financial health of millions while growing your career at a leading FinTech innovator.
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Work from anywhere in the U.S. with a collaborative, mission-driven team.
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We champion diversity, collaboration, curiosity, and integrity.
How to Apply:
If you are a strategic analytical leader passionate about using data to solve complex problems in consumer finance, we encourage you to apply—even if your experience doesn’t match every requirement.
Submit your application via Lever:Â https://jobs.lever.co/prosper/31d8121b-7760-490c-9cfe-9bfaa7547d67
Prosper is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All hiring decisions are based on merit, competence, and business need.