Head of Credit
I am currently working on an exciting technical Credit Leadership opportunity with a top-tier fintech. They are looking for a hands on data scientist with extensive experience in consumer credit risk modeling, acquisition models, and pricing models. The ideal candidate will have strong expertise in XGBoost, Python, and Scikit-learn, along with a proven track record of building or deploying decisioning models for credit cards, HELOC, or auto lending.
This is a high-impact opportunity to collaborate with top talent, leverage cutting-edge technology, and thrive in a fast-paced, innovative environment.
Key Responsibilities:
- Credit Modeling & Risk Management: Design, build, and deploy credit risk models to assess creditworthiness and predict default risks. Apply models to minimize credit losses.
- Strategic Decision-Making: Influence and guide the credit risk strategy for the portfolio. Tackle complex credit-related challenges and provide insights into credit risk and modeling.
- Influencing Credit Trends: Shape and influence credit trends in the portfolio, set new risk thresholds, re-evaluate risk policies, and introduce new methodologies.
- Leadership & Guidance: Mentor team members in credit risk and modeling. Establish high standards for credit modeling practices.
- Cross-Functional Collaboration: Collaborate with engineers, data architects, DevOps, and product managers to integrate models into the company's systems. Engage with external partners like regulators and investors.
Key Qualifications:
- At least 5 years in Credit Risk for Card Acquisitions, Loan Origination, Consumer Lending, or Risk Mitigation.
- Proven experience developing or deploying credit risk models, line sloping, early risk mitigation, or lifecycle risk projections.
- Hands-on experience as a practicing data scientist (modeling role).
- Background in top-tier universities (CS, Math, Physics preferred).
- Experience at leading banks, fintechs, or lending institutions.
- Mortgage/HELOC experience is a plus.
- Strong expertise in XGBoost, Python, and Scikit-learn.
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