Kafene is a leading point-of-sale financing partner dedicated to empowering flexible ownership solutions for underserved customers nationwide. By enabling our retail partners to offer flexible lease-to-own (LTO) purchase options for prime and non-prime consumers, Kafene helps merchants grow their customer base and meet the increasing demand for furniture, appliances, electronics, tires, and other durable goods. Utilizing over 20,000 data inputs alongside cutting-edge AI and machine learning technologies, our platform creates a best-in-class experience for both merchants and customers. With over $300 million in sales since inception, we are rapidly growing and looking to expand our team.
We take pride in fostering a dynamic workplace culture that values collaboration, innovation, and mutual support. Our team of 150 is spread across our NYC headquarters, a Wilmington office, and fully remote staff nationwide. Last year, we were recognized as one of Built In's Startups to Watch and Forbes' Best Startup Employers.
What You'll do:
- Develop reports to monitor our acquisition, portfolio, and collection performance related to consumer credit risk, fraud risk, lease amount, term, channel, and other important metrics across the account lifecycle.
- Merge complex data sources such as Bureau information, alternative data, consumer behavior, the macro environment, and internal portfolio performance metrics to capture a holistic view of portfolios and drive decisions accordingly.
- Leverage analytical tools (Python/R, SQL, etc.) to perform statistical and decision-tree analyses to identify root causes and potential business opportunities.
- Work with your manager to create summaries, presentations, and process documents to display results.
- Partner with the technology team to ensure timely and quality implementation with diligent test validation.
- Track and monitor existing risk strategies to improve financial performance, as well as enhance the experience for both customers and merchants.
Qualifications:
- Master’s degree in a quantitative discipline such as Statistics, Operations Research, Economics, Engineering, Data Science, or any other STEM major.
- 2+ years of prior risk strategy development experience in the LTO industry, or consumer financial lending industry.
- Experience utilizing Python/SQL for conducting statistical analysis and creating pivot tables.
Preferred Qualifications:
- Familiarity with decision-tree analysis tools such as Knowledge Seeker.
- Proficiency in other analytical/programming languages is a plus.
Compensation & Benefits:
- Base Salary: Earn a competitive base salary ranging from $90,000 to $150,000.
- 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.
Kafene is an equal-opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, and other legally protected characteristics. If you are applying for a job in the U.S. and need a reasonable accommodation for any part of the employment process, please send an e-mail to [email protected] and let us know the nature of your request and contact information. Please note that only those inquiries concerning a request for reasonable accommodation will be responded to from this email address.
Top Skills
What We Do
Kafene is a cutting-edge digital platform used by thousands of merchants at the point of sale to help offer underserved consumers more flexible purchase options through transparent lease-to-own (LTO) agreements that help retailers of furniture, appliances, electronics, tires, and other goods meaningfully broaden their addressable market. Kafene utilizes more than 20,000 data inputs in tandem with best-in-class artificial intelligence and machine learning technologies to underwrite, approve using efficient risk-based pricing, and enable payment in a near-instantaneous manner, while creating a best-in-class customer experience.
Why Work With Us
We create a win-win for consumers and retailers alike by offering debt-free, credit-building financing to an underserved consumer while helping retailers reach new customer segments. Our mission of doing well by doing good underlies everything about the culture we’ve built.