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)
About Stellantis
Stellantis is an Franco-Italian-American automotive holding company that manufactures automobiles.
