Principal Associate, Data Scientist - Anti-Money Laundering
Core
Developing predictive models, monitoring dashboards, and reporting to identify money laundering, fraud, terrorist financing, and human trafficking using advanced analytics and machine learning.
Role type
Principal Associate, Data Scientist (AML & GenAI)
Builds
Production ML models, monitoring dashboards, and reporting for AML programs
Domain
Financial Services / Anti-Money Laundering / Fraud Detection
Deliverable
production ML models
Required skills
Python, SQL, machine learning, statistical modeling, LLM fine-tuning, vector databases, RAG, LangGraph, LlamaIndex, AWS, Spark, dbt, clustering, classification, time series, deep learning
Preferred skills
AML modeling experience, GenAI/Agentic AI systems experience, AWS experience
Technologies
AWS, Snowflake, Python, Spark, Conda, dbt, LangGraph, LlamaIndex
Responsibilities
Partner with cross-functional teams to deliver risk management products; build production-ready pipelines for data sourcing and model scoring; develop and deploy ML models through design, training, evaluation, and implementation; fine-tune and productionize Large Language Models (LLMs)
Seniority
Principal, hands-on IC
