Risk Manager
Wilmington, Delaware
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 nonprime consumers, Kafene helps merchants grow their customer base and meet the growing demand for furniture, appliances, electronics, tires, and other durable goods. Utilizing more than 20,000 data inputs in tandem with cutting-edge AI and machine learning technologies, our platform creates a best-in-class experience for both merchants and customers. With over $200 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 100 is spread between a NYC headquarters, a Wilmington office, and fully remote staff across the country. Last year, we were selected for Built In Startups to Watch and Forbes' Best Startup Employers.
We take pride in fostering a dynamic workplace culture that values collaboration, innovation, and mutual support. Our team of 100 is spread between a NYC headquarters, a Wilmington office, and fully remote staff across the country. Last year, we were selected for Built In 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. Additionally, we contribute 75% of the premium for your spouse and/or 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.
- Monthly Mileage and Cell Phone Reimbursement: To ensure you can perform your duties effectively, we provide reimbursement for monthly mileage and cell phone expenses.
Job Profile
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401(k) Plan Competitive base salary Competitive salary Dynamic workplace culture Flexible paid time off Healthcare Healthcare coverage Mileage and cell phone reimbursement Paid Time Off Retirement benefits
Tasks- Create summaries and presentations
- Develop reports
- Leverage analytical tools
- Merge complex data sources
- Partner with technology team
- Track existing risk strategies
AI Data analysis Data Science Decision-Tree Analysis Machine Learning Python R Sales SQL Statistical analysis
Experience2 years
EducationData Science Economics Engineering Master's degree
TimezonesAmerica/Anchorage America/Chicago America/Denver America/Los_Angeles America/New_York Pacific/Honolulu UTC-10 UTC-5 UTC-6 UTC-7 UTC-8 UTC-9
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