Sr. Staff Data Scientist – Machine Learning & AI (Quality, Vehicle & Engineering Analytics)
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
- 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
- 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
- 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
- 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
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
Preferred QualificationsBasic 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)
- 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
Skills Required
- Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field
- Minimum of 8 years of experience in data science, advanced analytics, or machine learning
- Minimum of 5 years hands-on experience with Databricks, Palantir, Snowflake, or AWS SageMaker
- Expert-level proficiency in Python (or R)
- Expert-level proficiency in SQL
- Strong foundation in machine learning algorithms and statistical modeling
- Experience with neural networks / deep learning
- Experience building ML solutions on distributed systems (e.g., Spark)
- Master's degree in Computer Science, Computer Engineering, Electrical Engineering, or related field
- Experience with Large Language Models (LLMs) and fine-tuning foundation models
- Experience with agentic AI systems
- Experience building ML solutions in automotive, propulsion, or battery systems
- Strong understanding of vehicle quality, reliability, or manufacturing analytics
- Experience working in high-scale enterprise or regulated environments
- Proven impact from deployed ML systems or production analytics products
- Strong communication skills with executive and non-technical stakeholders
Stellantis Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Stellantis and has not been reviewed or approved by Stellantis.
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Pay Growth & Progression — Contract-driven increases lifted hourly wages roughly 25% over 4.5 years and restored cost-of-living adjustments, pushing top rates near $42 per hour by the end of the agreement. Union hourly positions appear to have benefited most since the 2023 deal.
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Affordable Benefits — UAW-represented hourly workers pay no premiums and about 3% of total healthcare costs while receiving comprehensive medical, dental, vision, and wellness coverage. This creates materially lower out-of-pocket costs for represented hourly roles.
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Retirement Support — Post-2007 hourly hires receive a 10% employer 401(k) contribution and legacy workers saw defined-benefit improvements with retiree bonuses. Salaried roles also cite a 401(k) with employer match and contribution up to a maximum of 8%.
Stellantis Insights
What We Do
Our storied and iconic brands embody the passion of their visionary founders and today’s customers in their innovative products and services: they include Abarth, Alfa Romeo, Chrysler, Citroën, Dodge, DS Automobiles, Fiat, Jeep®, Lancia, Maserati, Opel, Peugeot, Ram, Vauxhall and mobility brands Free2move and Leasys. Powered by our diversity, we lead the way the world moves – aspiring to become the greatest sustainable mobility tech company, not the biggest, while creating added value for all stakeholders as well as the communities in which we operate.
