Stellantis

Sr Staff Data Scientist

Stellantis$130K — $180K *
Enterprise Technology
8 - 10 years of experience
Job Overview by Ladders

Qualifications

  • Master or PhD Degree with a technical focus
  • 8+ years of experience in advanced analytics/machine learning
  • 5+ years of experience with Databricks, Palantir, Snowflake, or AWS SageMaker
  • Expert proficiency in Python (or R) and SQL
  • Deep knowledge of statistical methods, ML algorithms, and neural networks
  • Experience with distributed data processing platforms like Spark

Responsibilities

  • Own and evolve the ML & AI framework for quality and engineering products
  • Set technical direction for data architecture aligned to business strategy
  • Lead development of predictive and causal models using vehicle and enterprise data
  • Design LLM-based systems for engineering applications
  • Architect scalable data pipelines and analytics systems
  • Lead model lifecycle management and validation in production environments
  • Drive experimentation and translate results into product decisions

Benefits

  • Global company presence with diverse work culture
  • Opportunity to make a significant impact on product quality and customer experience
  • Mentoring opportunities to influence the skills of mid-level data scientists
  • Contributions to a centralized knowledge base and external technical community
  • Involvement in cutting-edge mobility solutions, including electrification and autonomous driving
Full Job Description
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.


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

About Stellantis

Stellantis is a multinational automotive manufacturer formed in 2021 by the merger of Fiat Chrysler Automobiles and Groupe PSA. The company designs, produces, and sells a wide range of vehicles under various brands, including Alfa Romeo, Chrysler, Citroen, Dodge, DS Automobiles, Fiat, Jeep, Lancia, Maserati, Opel, Peugeot, Ram, and Vauxhall. Stellantis operates in over 130 countries and has 14 brands in its portfolio. The company is committed to sustainable mobility and has set ambitious targets for reducing its carbon footprint and increasing the share of electric vehicles in its sales.
Learn more about Stellantis
Size
400,000 employees
Market Cap
$44.9 billion
Industry

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