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Skip to content Владимир Карамазов представя първата си фотокнига в София и Орешак Николаос Цитиридис тръгва на турне в страната Европейският музикален фестивал представя 7 концерта през есента Ерика Баду с нов студиен албум малко преди концерта си в София Torino & Pashata и Evangelia представят…

Get to Know 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 origination s and counting. But we're just getting started.

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.

Ready to be part of the fintech revolution? Join us.

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.

What You’ll Do

  • 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

What You’ll Bring

  • 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

Compensation and Benefits:

  • Base Salary: Earn a competitive base salary $127,500 - $140,000

  • 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.

We're building a team as diverse as the customers we serve. Kafene is proud to be an equal-opportunity employer, and we mean it. We welcome qualified applicants of every race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, veteran status, and all other legally protected characteristics.

Need accommodation during the application process? We've got you. If you're applying for a U.S. position and require reasonable accommodation at any stage, reach out to [email protected] with details about your request and contact information. We're here to help make the process work for you.

Note: This email address is specifically for accommodation requests and will only respond to those inquiries.

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