We are looking for a Machine Learning Engineer / Data Scientist to develop advanced statistical models and simulations that drive Vehicle Configuration Optimization (VCO). This role will leverage curated datasets to build a customer-level preference simulation engine, enabling optimized vehicle order guides (VOGs) for future model years.

This is a highly impactful role for an early-to-mid career data scientist who enjoys combining statistical rigor, large-scale data, and real-world business impact.

Key Responsibilities:

• Build and run large-scale simulations (e.g., 50,000 synthetic customers) to model vehicle purchase behavior
• Develop statistical and machine learning models using Databricks
• Leverage datasets including:
• • Historical vehicle sales
  • Competitive sales data
  • Feature-level willingness-to-pay data
  • Customer preference models
• Translate model outputs into optimized Vehicle Order Guides (VOGs) that inform product configuration decisions
• Perform exploratory data analysis and feature engineering on complex datasets
• Collaborate closely with Data Engineering to refine and leverage curated datasets
• Communicate insights and model recommendations to business stakeholders
• Continuously evaluate and improve model accuracy and assumptions