Senior Fraud Data Scientist
Tasks
- Automate model retraining and performance tracking
- Build and maintain MLOps pipelines for continuous integration deployment and monitoring
- Collaborate with fraud risk data engineering IT and business teams
- Conduct stress testing and validation with fraud operations collaboration
- Deploy fraud models using SAS SFD and integrate with production systems
- Develop and optimize card fraud detection models
- Ensure models meet business and regulatory requirements
- Validate test and benchmark model performance
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | Azure | CI/CD | GCP | Kubeflow | MLOps | MLflow | Machine Learning | PyTorch | Python | SAS | SAS SFD | SQL | Scikit-learn | TensorFlow
Education
Roles
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