Risk Manager

About Us

Kafene is revolutionizing the lease-to-own space. We're the point-of-sale powerhouse making flexible lease-to-own accessible to everyone—prime and non-prime customers alike. Our secret weapon? Cutting-edge AI and machine learning that analyzes 20,000+ data inputs in real-time, empowering retailers across furniture, appliances, electronics, tires, and durable goods to say "yes" to more customers. The numbers tell our story: over $500 million in originations and counting. Our 150-person team spans NYC headquarters, Wilmington, and remote talent across the globe—all united by a culture that thrives on collaboration, innovation, and genuine support. We don't just talk about great workplace culture; we deliver it. That's why Built In named us a Startup to Watch and Forbes recognized us as one of the Best Startup Employers.

About The Team

Kafene’s Risk team is a key driver of growth for the business. As a Risk Manager, you will report to the VP of Risk and help build Kafene’s profit-driven consumer underwriting strategies. You will harness complex data sources and machine learning, and you will partner across technology and senior leadership to develop strategies that optimize credit risk, fraud risk, and other factors across underwriting, portfolio management, and collections.

Responsibilities

• Monitor acquisition, portfolio, and collection performance across the account lifecycle, with a focus on consumer credit risk, fraud risk, lease terms, channel performance, and other key metrics
• Integrate complex data sources, including bureau, alternative, behavioral, macroeconomic, and internal portfolio data, to generate actionable insights
• Conduct statistical and decision-tree analyses to identify root causes and business opportunities
• Present findings to leadership, partner with technology teams to support strategy implementation and validation, and continuously monitor risk strategies to improve financial performance and enhance the customer and merchant experience

Requirements

• Master of Science degree with major in a quantitative discipline (Statistics, Economics, Business/Data Analytics, or similar)
• 18 months'+ work experience building quantitative and statistical models in the consumer financial lending or lease-to-own (LTO) industry
• Experience must include leveraging Python, R, and Excel for statistical analysis and creating pivot tables and using decision-tree modeling tools for predictive analysis

Benefits

• Healthcare: We prioritize your well-being by covering 80% of medical, dental, and vision insurance costs, including coverage for your spouse, children, and other dependents.
• Retirement Benefits: Begin planning for your future from day one with our 401k plan.
• Paid Time Off: We understand the importance of work-life balance. That's why we offer flexible paid time off days starting from day one of your employment.

Pay

Base Salary: $127,500 – $140,000