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What You'll Do:
- Feature Engineering: Mine internal and external datasets for high-signal features like DTI and PTI to improve credit models.
- Model Development: Own end-to-end development of strategic credit risk models for approvals, credit lines, and loss forecasting.
- Vendor Evaluation: Assess third-party data vendors and lead cost-benefit analyses for integration.
What You'll Bring:
- Education: Master's or PhD in a quantitative field like Statistics or Data Science.
- Experience: 5+ years in data science or ML with focus on credit risk or financial analytics.
- Technical Skills: Advanced Python, strong SQL, expertise in gradient boosting, ensemble methods, and AutoML.
Why Kafene:
- Direct impact on credit outcomes for hundreds of thousands of customers.
- Own full ML lifecycle from data to production.
- ML is a strategic asset; competitive salary and remote flexibility.
Kafene
Kafene is a fintech company revolutionizing lease-to-own with AI and machine learning. With over $500 million in originations, our 175-person team operates from NYC and globally, fostering a collaborative culture recognized by Built In and Forbes.