Grow your revenue with Kafene. Attract and convert customers from all credit profiles with flexible lease-to-own programs. Backed by Gaingels.
About the role
Feature Engineering: Go beyond surface-level signals — you'll mine internal and external datasets to engineer high-signal features (DTI, PTI, payment behavior, account balance patterns) that directly improve the predictive power of production credit models. Your work here changes approval outcomes for real customers. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- Advanced Python for statistical modeling and ML — not primarily for application development or infrastructure engineering
- Strong SQL for data extraction and feature construction
- Deep expertise in ML algorithms purpose-built for structured/tabular data: gradient boosting, ensemble methods, regression models, decision trees, and AutoML frameworks
- Industry Background: Prior experience in consumer lending, fintech, or financial services is highly preferred, you should already understand what DTI, PTI, and vintage analysis mean without needing context
- Governance: Hands-on experience with model risk governance frameworks and working alongside validation teams, you know the SR 11-7 world and aren't intimidated by it
- Communication: You can explain a gradient boosting model to a risk committee and a credit policy tradeoff to an engineer. Both matter here
More about this role
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. But we're just getting started .
Our 175-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.
Credit and risk are at the heart of our business. We're looking for a Manager of Data Scientist, a senior individual contributor who will own the full lifecycle of the ML models that power our credit risk decisions. Reporting directly to the VP of Risk, you'll design, build,...
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