Data Science Lead - AML Risk

Tasks

• Build AML detection coverage frameworks
• Build decisioning layers for precision recall tradeoffs
• Create investigator insight systems
• Design manual data labeling projects
• Develop AML detection controls
• Evaluate AML systems against benchmarks
• Hire and mentor data science specialists
• Implement scheduled data gathering and model retraining
• Maintain production grade Python services
• Package algorithms into deployable libraries
• Provide data driven scenario insights
• Refine operational feedback integration
• Transition models from staging to production

Perks/Benefits

• N/A

Skills/Tech-stack

Experiment design | Financial Crime domain | Financial crime | GenAI | Language Models | Large Language Models | Machine Learning | Object-Oriented | Object-oriented programming | Precision-recall | Python | Semi-Supervised Learning | Semi-supervised | Statistical Analysis | Supervised Learning | Unsupervised Learning