Senior Machine Learning, Data Science Engineer (R-19593)
Tasks
- Apply large language models for credit risk fraud detection and compliance
- Build risk signals from structured data
- Build risk signals from unstructured data
- Calibrate document and monitor risk models
- Collaborate with stakeholders on modeling engagements
- Communicate model results to technical and non-technical audiences
- Design develop and validate risk models
- Develop AI agents for autonomous risk detection
- Develop B2B risk solutions
- Develop machine learning models for predictive risk monitoring
- Implement real-time anomaly detection
- Use natural language processing for risk triggers and insights
Perks/Benefits
- N/A
Skills/Tech-stack
Anomaly Detection | Decision Tree | LLMs | Language Processing | LightGBM | Logistic Regression | Machine Learning | Model Validation | Natural Language | Natural Language Processing | Neural Network | Neural Networks | Prompt engineering | PySpark | Python | Random Forest | Risk Modeling | SQL | Scorecard Development | Statistical Analysis | XGBoost
Education
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