Senior Data Scientist/ML Engineer - Financial Crime
Tasks
- Analyze AML risk score drivers
- Build production ML systems
- Conduct sensitivity tests
- Create model documentation for audits
- Deploy and monitor ML models
- Engineer AML and fraud features
- Implement model lifecycle software
- Manage model versioning and rollback
- Monitor drift and model health
- Own batch training pipelines
- Partner with risk compliance stakeholders
- Produce model cards and ML governance artifacts
- Run back testing
- Set calibrated alerting thresholds
- Test and operate model pipelines
- Track model and operational metrics
- Train transaction monitoring models
- Translate domain knowledge into signals
Perks/Benefits
- Annual L and D budget
- Corporate pension scheme
- Paid time off
- Referral bonus
- Sabbatical
- Virtual stock options
Skills/Tech-stack
Alerting | Anomaly Detection | Automated testing | Back Testing | CI/CD | Clustering | Code review | Data Lineage | Data Quality | Feature Engineering | Feature Stores | Incident Response | Machine Learning | Model Cards | Model Deployment | Model Drift | Model Monitoring | Model Registry | Model Training | Model Validation | Observability | Python | Reproducibility | Rollback | Sensitivity Analysis | Technical documentation | Transaction monitoring
Education
N/A
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