Description
Checkout.com is hiring a Fraud Data Scientist to protect its ecosystem from sophisticated financial fraud and abuse. The role owns the end-to-end machine learning lifecycle, including developing and deploying real-time models, building agentic workflows and LLM-driven orchestration, conducting adversarial analysis, engineering streaming and batch features, and establishing shadow testing, A/B testing, and monitoring pipelines. The position requires at least three years of applied data science experience, production machine learning expertise, strong Python and SQL skills, cloud data experience, and familiarity with MLflow and Airflow. It follows a hybrid model with three days per week in the office.
