Sr. Staff Data Scientist Machine Learning & AI (Quality, Vehicle & Engineering Analytics)

Sr. Staff Data Scientist - Machine Learning & AI (Quality, Vehicle & Engineering Analytics) Full Time Auburn Hills, MI, United States Posted 4 days ago

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Sep 14, 2026 Stellantis Category Software Engineers/Developers Tags Industry Language Modeling Neural Networks NLP QA United States Share This Click to share on LinkedIn (Opens in new window) Click to share on Facebook (Opens in new window) Click to share on Twitter (Opens in new window) More Click to share on Reddit (Opens in new window) Click to share on Pinterest (Opens in new window) Click to share on Tumblr (Opens in new window) Click to share on Pocket (Opens in new window) Apply for job Login to bookmark this Job Overview About the

Role:

We are looking for a Senior Staff Data Scientist (ML/AI) to serve as a technical leader, architect, and individual contributor within the Machine Learning & AI Engineering team at Stellantis. This role sits at the intersection of machine learning, advanced analytics, experimentation, and large-scale vehicle/IoT data systems. You will define and influence how ML and AI are used across vehicle quality, engineering systems, and customer experience outcomes. This is a high-impact, senior IC role (Staff/Principal level influence) responsible for shaping technical strategy, designing scalable ML systems, and driving measurable business outcomes such as quality improvement, warranty reduction, and customer experience enhancement.

What You Will Do:

Technical Leadership & ML Strategy (Staff-Level Ownership) Define and evolve the ML/AI architecture and framework supporting quality, engineering, and vehicle analytics across the organization Set technical direction for: Machine learning systems Experimentation platforms Data science architecture Act as a trusted technical advisor to senior leadership on: Model feasibility Trade-offs (accuracy, scalability, cost, interpretability) Business impact of ML/AI initiatives Influence roadmap decisions across engineering and product organizations Advanced Machine Learning & Statistical Modeling Develop and deploy predictive, prescriptive, and causal models using: Vehicle data IoT sensor data Enterprise datasets Apply advanced techniques including: Statistical modeling Machine learning algorithms Deep learning / neural networks Lead root cause analysis for vehicle quality, performance, and system failures Design and build LLM-based systems and agentic AI solutions for engineering and quality use cases Data Science Platform & Scalable Systems Architect and guide development of large-scale distributed data and ML systems Build and scale analytics pipelines using Spark-based distributed processing frameworks Lead ML model lifecycle management, including: Training Validation Deployment Monitoring in production Ensure models and systems are: Explainable Reliable Production-ready Compliant with automotive/regulatory standards Experimentation & Product Impact Own and evolve the experimentation framework/platform for safe, scalable testing of vehicle and software features Design statistically sound experiments (A/B tests and beyond) Translate experimental results into clear product and engineering decisions Drive measurable business outcomes including: Warranty cost reduction Improved product quality Enhanced customer experience Revenue-impacting insights Influence, Mentorship & Knowledge Sharing Mentor senior and mid-level data scientists, raising technical standards across the team Help teams with: Problem formulation Research design Statistical interpretation Contribute to internal knowledge systems and external-facing technical content (e.g., blogs or papers) Serve as a cross-functional leader bridging engineering, product, and executive teams What Success Looks Like (Top Performers) Strong candidates will demonstrate: Proven impact from deployed ML systems or production analytics products Quantifiable improvements in: Vehicle quality Warranty reduction Customer experience metrics Ability to influence technical strategy beyond their immediate team Strong communication skills with executive and non-technical stakeholders Demonstrated ability to turn complex analysis into business decisions and outcomes

Basic Qualifications:

Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field A minimum of 8 years of experience in data science, advanced analytics, or machine learning, including a minimum of 5 years of hands-on experience with Databricks, Palantir, Snowflake, or AWS SageMaker Expert-level proficiency in: Python (or R) SQL Strong foundation in: Machine learning algorithms Statistical modeling Neural networks / deep learning Experience building ML solutions on distributed systems (e.g., Spark)

Preferred Qualifications:

Master's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field Experience with: Large Language Models (LLMs) Fine-tuning foundation models Agentic AI systems Experience building ML solutions in engineering, automotive, propulsion, or battery systems Strong understanding of vehicle quality (QA), reliability, or manufacturing analytics Experience working in high-scale enterprise or regulated environments

Company:

Stellantis Qualifications:

Language requirements: Specific requirements: Educational level: Level of experience (years): Senior (5+ years of experience) Tagged as: Industry , Language Modeling , Neural Networks , NLP , QA , United States About Stellantis Stellantis is an Franco-Italian-American automotive holding company that manufactures automobiles. Related Jobs Principal Machine Learning Engineer, AI & Data Platforms (AiDP) Apple Inc. New Addington, United Kingdom, United Kingdom Full Time Posted 1 day ago

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