Data Scientist – Fleet Data

Mission:
Lead data analytics activities for fleet monitoring and tool evolution, applying AI and advanced analytics to process and analyze vehicle data collected through JARVIS and support system improvements.

Key Responsibilities:

• Identify upcoming fleets for the region and determine the necessary BDCs and signals for tracking.
• Define and monitor specific KPIs for fleet monitoring.
• Use AI, machine learning, and data analytics tools to process and analyze JARVIS vehicle data and identify meaningful trends, anomalies, and performance insights.
• Organize pre-production sample testing after the first vehicle is equipped, in collaboration with Data Science teams.
• Ensure fleet data is properly published and available within the required systems.
• Participate in weekly fleet-management and safety-steering meetings, coordinating issue resolution with local teams (HMT,suppliers, and IT)
• Review and analyze Mileage traveled by each fleet, summarize issues, and recommend improvements.
• Support JARVIS deployment and test new features and KPIs.

Provide technical direction, coaching, and guidance to junior engineers in the U.S. and other regions supporting North American vehicle-data activities.

Basic Qualifications:

• Bachelor’s degree in Data Analytics, Data Science, Artificial Intelligence, Computer Science, Electrical Engineering, or a related engineering field
• A minimum of 8 years of work experience
• Experience with Genie, AI/ML tools, Python code, and advanced data analytics.
• Strong understanding of fleet operations and vehicle signals used for KPI development.
• Knowledge of vehicle electronic architectures and signal variations across fleets.

Preferred Qualifications:

• Master’s degree in Data Analytics, Data Science, Artificial Intelligence, Computer Science, Electrical Engineering, or a related engineering field
• Experience in Databricks
• Experience with SI Roulage, JARVIS, Aptiv, or comparable fleet-monitoring and data-acquisition tools.
• Strong analytical, problem-solving, communication, and cross-functional collaboration skills.
• Ability to work independently and provide technical leadership across regional teams.