Lead, Financial Crime Data Science & Data Engineering
US GA ATL 201, United States
USD 108K-171K (estimate) Senior-level Full Time
Tasks
- Define data quality and validation standards
- Define detection strategies
- Deliver infrastructure for detection logic needs
- Design real-time pipelines
- Design scalable batch pipelines
- Develop validate deploy detection logic
- Enforce data lineage
- Ensure detection explainability
- Ensure detection logic governance documentation
- Establish detection performance metrics
- Execute end to end detection lifecycle
- Identify emerging fraud patterns
- Lead and develop data science and engineering teams
- Maintain alignment with operational workflows
- Monitor retrain optimize detection logic
- Own detection logic performance
- Partner with fraud operations and compliance
- Perform change management for detection logic
- Prioritize test deploy optimize detection controls
- Refine detection using performance and investigations
- Support Model Risk Management validation
- Support regulatory compliance for AML
- Support regulatory reporting pipelines
- Translate insights into detection improvements
- Translate regulatory requirements into detection logic plans
Perks/Benefits
- N/A
Skills/Tech-stack
AML Compliance | BSA/AML | Batch Processing | Credit Risk | Data Lineage | Data Pipelines | Data Quality | Data Validation | ELT | ETL | Explainable AI | False Positives | Fraud Detection | Machine Learning | Model Monitoring | Model Risk Management | Model risk | OFAC | Precision-recall | Python | Real Time | Real-time Processing | Retraining | Risk Management | SQL | Statistics | Time processing | Transaction monitoring
Education
Bachelor of Engineering | Bachelor of Science | Master of Engineering | Master of Science | PhD
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