The role involves leading improvements to pricing algorithms and applied machine learning systems. The individual will identify opportunities, shape research approaches, and manage the end-to-end lifecycle of models. Responsibilities include building, validating, and deploying machine learning solutions into production environments. The position requires analyzing market and vehicle data to optimize business outcomes such as margin and conversion. Additionally, the role contributes to machine learning domains including lending, fraud detection, and recommendation systems.

Candidates must possess at least eight years of experience as a data scientist with a history of delivering measurable business impact. Proficiency in Python and the ability to manage the full machine learning lifecycle from exploration to production deployment are required. Applicants need strong statistical fundamentals and the ability to navigate high-ambiguity environments with strategic autonomy. The role also requires excellent communication skills to translate technical findings into business recommendations.