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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.
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.
At Stellantis, we assess candidates based on qualifications, merit, and business needs. We welcome applications from all people without regard to sex, age, ethnicity, nationality, religion, sexual orientation, disability, or any characteristic protected by law. We believe that diverse teams reflect our identity as a global company, enabling us to better address the evolving needs of our customers and care for our future.
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Stellantis
Nov 06, 2026