Associate Data Scientist - Anti-Money Laundering Analytics & Modeling
Core
Build statistical models and algorithms to detect, monitor, and avert concerning patterns of account activity and transactional data to support Anti-Money Laundering (AML) strategies.
Role type
Associate Data Scientist (AML Analytics & Modeling)
Builds
Production ML models for fraud and AML detection within banking systems
Domain
Banking / Financial Services / Anti-Money Laundering
Deliverable
production ML models
Required skills
Logistic regression, Clustering, Gradient boosting, Neural networks, Python, PySpark, R, SQL, Statistical methods, Data mining, Data preparation
Preferred skills
Banking/financial services experience, Anti-fraud/AML modeling, Cloud platforms (AWS, Google Cloud, Azure), Model validation, Model implementation
Technologies
Python, PySpark, R, SQL, AWS, Google Cloud, Azure
Responsibilities
Extract usable information from customer, account, and transactional data sets; Participate in data set creation, analysis, reporting, model building, model monitoring and model documentation; Design samples and build statistical models using machine learning algorithms; Present complex technical concepts to non-technical stakeholders and senior executives
Seniority
Associate (0-2 years experience)
