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Sr Staff Data Scientist

Stellantis
Posted 10 days ago, valid for 17 days
Location

Auburn Hills, MI 48321, US

Salary

Competitive

Contract type

Full Time

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Sonic Summary

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  • The Machine Learning & AI Engineering Team is seeking a Sr Staff Data Scientist to lead technical efforts across quality, engineering, and vehicle data domains.
  • This role requires a Master or PhD degree and a minimum of 8 years of total experience in data-oriented advanced analytics or machine learning, with at least 5 years on platforms like Databricks or AWS SageMaker.
  • The position emphasizes technical leadership, advanced analytics, and experimentation, aiming to influence product quality and customer experience.
  • Candidates should have expert-level proficiency in Python or R, SQL, and a deep understanding of statistical methods and ML algorithms.
  • The salary for this role is not specified, but it is expected to align with senior-level positions in the industry.

Your Mission:

The Machine Learning & AI Engineering Team is looking for a Sr Staff Data Scientist to act as a technical thought leader and architect across quality, engineering, and vehicle data domains. This role owns the design, evolution, and application of advanced ML, AI, and experimentation systems that directly influence product quality, customer experience, and measurable business outcomes. This is a senior individual contributor role with enterprise-wide influence, expected to shape strategy, mentor others, and partner closely with engineering, product, and leadership

 

Priorities can change in a fast-paced environment like ours, so this role includes, but is not limited to the following responsibilities:

Technical Leadership & Strategy:

  • Being the trusted expert who own and evolve the ML & AI framework supporting quality and engineering products across the organization.
  • Set technical direction for modeling, experimentation, and data architecture aligned to business and product strategy
  • Serve as a trusted advisor to senior stakeholders on ML/AI feasibility, tradeoffs, and impact

 

Advanced Analytics & Modeling:

  • Lead development of predictive, prescriptive, and causal models using vehicle, IoT, and enterprise data.
  • Apply advanced statistical, ML, and deep learning techniques to root cause analysis, quality improvement, and feature optimization.
  • Design and refine LLM-based and agentic systems for engineering and quality applications.

 

Data & Platform Architecture:

  • Architect and guide implementation of scalable data pipelines and distributed analytics systems (Spark-based).
  • Lead model lifecycle management, validation, and performance governance in production environments.
  • Ensure solutions are robust, explainable, and suitable for regulated automotive contexts.

 

Experimentation & Product Impact:

  • Lead the experimentation platform and methodology, enabling safe, agile testing of software and vehicle features.
  • Translate experimental results into actionable product and engineering decisions.
  • Drive measurable outcomes in revenue, warranty cost reduction, and customer experience.

 

Knowledge Sharing & Influence:

  • Democratize learning through contributions to a centralized internal knowledge base and external technical blog.
  • Mentor senior and mid-level data scientists; raise the overall technical bar of the organization.
  • Educate partners on problem formulation, research design, and interpretation of results.

 

Top Performers will be able to demonstrate:

  • Demonstrated business impact through deployed models or analytics-driven products.
  • Measurable improvements in quality, warranty cost, or customer experience.
  • Clear influence on technical direction beyond immediate project scope.
  • Effective communication and alignment with non-technical and executive stakeholders.
  • Measurable consumer experience impact through analysis, statistical models or products built.

 

Your Platform:
 

A truly global company, we have headquarters in Amsterdam, Paris, Turin, and Auburn Hills. We also have technology hubs on the east and west coast of the United States, in South America and India. These locations are the nerve center of our company, where the best ideas combine with unrivalled rigor to create the biggest and best automotive experiences in the world.

  

Our World:
  
 

Great mobility solutions start with great people!  This is an exciting time to join us!  

 

Stellantis is a leading global mobility player guided by a clear mission: to provide freedom of movement for all through distinctive, appealing, affordable and sustainable mobility solutions. Our Company’s strength lies in the breadth of our iconic brand portfolio, the diversity and passion of our 300,000 people, and our deep roots in the communities in which we operate.

 

In this new era of mobility, our portfolio of brands is uniquely positioned to offer distinctive and sustainable solutions to meet the evolving needs of customers, as they embrace electrification, connectivity, autonomous driving and shared ownership. Founded by visionaries who infused them with passion and competitive spirit, these brands have made automotive history for more than a century and continue to speak to customers and inspire our employees today.

 

The driving force behind us is the diverse and talented group of men and women around the world who bring their passion and experience to their work every day. And while we are a truly global organization, we remain deeply rooted in the communities in which we operate and our people live and work.

 

Qualifications

Required Qualifications:

  • Master or PhD Degree required with technical focus (e.g. Data science, Statistics, CS, Physics, Engineering, etc.) 
  • 8+ years of total experience in data-oriented advanced analytics/ machine learning
  • 5+ years of intensive experience on Databricks, Palantir, Snowflake or AWS SageMaker.
  • Expert-level proficiency in Python (or R) and SQL for feature engineering and modeling.
  • Deep knowledge of statistical methods, ML algorithms, and neural network–based systems.
  • Experience designing solutions on distributed data processing platforms (Spark).

 

Preferred Qualifications:

  • Expertise in LLM fine-tuning, agentic systems, or ML systems for engineering use cases
  • QA Knowledge for vehicle, propulsion and battery components



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