This role focuses on developing and enhancing machine learning models to detect and prevent financial crimes like money laundering and sanctions violations
Job Summary
This role focuses on developing and enhancing machine learning models to detect and prevent financial crimes like money laundering and sanctions violations.
The ideal candidate will work hands-on with large datasets to identify patterns, anomalies, and risk indicators while ensuring solutions remain explainable and auditable.
State Street offers a collaborative global environment where employees can grow technical skills and contribute to the company's digital transformation using advanced AI technologies.
Matching Summary
This role focuses on developing and enhancing machine learning models to detect and prevent financial crimes like money laundering and sanctions violations.
Salary
Base: $80,000 - $140,000 Annual; Bonus/Equity: Eligible for annual performance-based awards; Benefits: Comprehensive program including 401K match, insurance, and paid time off
Skills & Requirements
Must-have
Machine learning model development
Python and SQL data analysis
Anti-Money Laundering (AML) domain knowledge
Financial transaction data experience
Agile project delivery practices
Nice-to-have
Experience with SWIFT message formats
Knowledge of LexisNexus or Firco tools
Fedwires transaction understanding
Strong stakeholder communication skills
Interest in regulated financial environments
Key Requirements
5-6+ years of financial services experience
Bachelor's degree in Engineering, Business, or Technology
Proficiency in Python and SQL for data modeling
Deep understanding of AML, Sanctions, and KYC principles