Remote role (United States) responsible for building Python-based analyses, classification models, and data pipelines to support fraud decisioning; designing and running statistical experiments; monitoring model performance and vendor evaluation; and developing dashboards in Looker and Hex. Requires 3+ years in fraud analytics or quantitatively demanding roles and strong skills in Python, SQL, and statistical experimentation.

Join a team bridging research and production to build ML infrastructure (feature stores, model serving, real-time inference) and deploy models at scale. The role embeds with product engineering teams to translate experimental models into production-ready systems and solve domain problems like pricing optimization, demand forecasting, and fraud detection. Requires strong software engineering and production ML experience.