Manager of Data Science, Credit & Fraud Risk Modeling
New
K
KafeneFintech, Credit Risk
RemoteFull-TimeManager
Salary95,000 - 140,000 USD per year
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Job Details
- Experience
- 5+ years
- Required Skills
- PythonSQLMachine LearningData science
Requirements
- Master's or PhD in Statistics, Mathematics, Data Science, Econometrics, or a related field.
- 5+ years of experience as a Data Scientist or ML Engineer with a focus on predictive modeling.
- Proven experience in credit risk, fraud detection, or financial analytics within consumer lending or fintech.
- Advanced Python proficiency for statistical modeling and machine learning.
- Strong SQL skills for data extraction and feature construction.
- Deep expertise in gradient boosting, ensemble methods, regression models, decision trees, and AutoML frameworks.
- Hands-on experience with model risk governance frameworks and validation teams (e.g., SR 11-7).
- Ability to communicate complex technical concepts to non-technical stakeholders like risk committees.
- Demonstrated experience deploying models that directly impact credit or lending decisions.
Responsibilities
- Mine internal and external datasets to engineer high-signal features including DTI, PTI, payment behavior, and account balance patterns.
- Develop end-to-end strategic credit risk models for approval amount sensitivity, credit line optimization, and loss forecasting.
- Source, clean, and transform financial data into modeling-ready datasets, ensuring data integrity.
- Evaluate third-party data vendors and scoring products through cost-benefit analyses.
- Implement models into production, ensuring accurate and efficient deployment in collaboration with engineering.
- Monitor model performance in production, leading recalibration and redevelopment as needed.
- Ensure model compliance with regulatory requirements and risk governance frameworks.
- Translate complex business questions from risk, finance, and sales into actionable modeling solutions.
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