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Overview: In this role you will oversee the validation and governance of credit risk, fraud risk, and line management models to ensure soundness and regulatory compliance. You will collaborate with cross-functional partners and regulators to elevate model risk management and adapt governance as modeling techniques evolve. The position offers intellectual growth at scale within a risk-focused culture that upholds trust and security. You will influence risk decisions and help shape the enterprise-wide approach to model risk.
Responsibilities: Oversee credit risk, fraud risk, and line management models including conceptual soundness, data quality, performance validation, and ongoing monitoring Document detailed model review reports for regulatory and internal audits Communicate model review results to business partners, senior leaders, and regulators Evaluate machine learning algorithms and their application in models Enhance governance framework to accommodate evolving modeling techniques and risk management
Key requirements: Advanced degree in quantitative fields Hands-on modeling experience preferred Knowledge of machine learning algorithms (e.g., gradient boosting, XGBoost, neural networks) and classical statistical methods Experience with large data processing; familiarity with big data platforms and tools (e.g., Hadoop, Pig, Hive, Spark, AWS) Proficiency in Python/R; Java/Scala/C++ a plus Strong communication and written skills Flexibility and adaptability to tight deadlines and changing priorities Strong communication Adaptability Attention to detail Python R XGBoost

Also on the board Same function, level within a rung

Level

Manager

Location

Brooklyn, NY

Occupation

Data Scientists

Industry

Other Scientific and Technical Consulting Services

Posted

today

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