Lead development of a greenfield data product by partnering with customers and product teams to build analytics and models (simulation, Bayesian networks, optimization, ML). Maintain existing analytics, improve predictive churn models, and translate customer needs into production-grade SQL/dbt pipelines, dashboards, and data-driven product features.

The Machine Learning Engineer will design, build, and maintain production machine learning systems, focusing on scalability, reliability, and integration with existing products. Responsibilities include developing ML pipelines, establishing ML Ops best practices, and collaborating on product capabilities.