CCB Risk Modeling Data-Scientist Sr Associate Fraud Prevention

Hands-on individual contributor role focused on building and scaling fraud prevention ML capabilities in an AWS environment. You’ll develop, deploy, monitor, and optimize predictive models for fraud/risk, explore and implement advanced approaches (e.g., graph networks, LLMs, agentic AI), and build/test reliable AI agents end-to-end. You’ll also create data pipelines and insight tooling using Databricks/PySpark, partner closely with product/engineering/data science, contribute reusable firmwide solutions and best practices, and mentor junior team members. Ideal candidates have 5+ years of model development in financial services, strong ML fundamentals (classical + deep learning), and are proficient in Python and SQL/PySpark (PyTorch/TensorFlow; XGBoost/sklearn), with AWS and large-scale data experience; graph analytics/GSQL is a plus.