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About

Jen is a principal machine learning engineer specializing in production ML systems and strategic AI/ML implementation across enterprise operations. As a seasoned leader with extensive advanced analytics experience, she architects end-to-end machine learning tools that transform complex operational challenges into predictive intelligence. Her expertise spans forecasting systems, intelligent automation pipelines, and MLOps infrastructure in high-risk industrial environments.
Jen has led ML engineering initiatives at Raytheon Technologies, Rolls-Royce, and BMW, building models and scalable pipelines into production that optimize mission-critical operations.

Originally drawn to data through an engineering background and curiosity about how complex systems work, she now applies herself to designing robust ML infrastructure. Her tech stack includes Python, cloud-native ML platforms, and distributed computing frameworks to build real-time inference systems, automated model monitoring, and strategic analytics tools. Jen holds a degree in Data Science from New York University.