Über
The Machine Learning & AI Engineering team is looking for a Staff Data Scientist to independently deliver advanced analytics and machine learning solutions across quality and engineering domains.
This role focuses on strong technical execution, applied modeling, and cross-functional collaboration to solve complex quality and engineering problems using established ML and AI approaches. The Staff Data Scientist IV contributes to shared frameworks, experimentation practices, and reusable assets, while operating under the broader technical direction set by Senior Staff and Principal-level leaders.
Key
Responsibilities
Advanced Analytics & Modeling Design, develop, and deploy predictive and statistical models using vehicle and enterprise data. Apply advanced analytics and ML techniques to root cause analysis, quality improvement, and feature optimization. Support development of LLM based or ML driven solutions for engineering and quality use cases, leveraging existing architectures and patterns. ML Systems & Data Platforms
Build and maintain scalable data pipelines and ML workflows using distributed data platforms (e.g., Spark based systems). Contribute to the evolution of shared ML frameworks, tooling, and best practices. Ensure models and analytics solutions are robust, explainable, and suitable for regulated automotive contexts. Experimentation & Product Support
Support experimentation methodologies and platforms to enable safe and effective testing of software and product features. Analyze experimental results and translate findings into actionable recommendations for engineering and product teams. Partner with stakeholders to define success metrics and validate model impact. Collaboration & Knowledge Sharing
Work closely with engineering, quality, and product partners to translate business problems into data science solutions. Clearly communicate analytical findings to both technical and non technical audiences. Document methodologies and contribute to centralized knowledge repositories. 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.
Top Performers will be able to demonstrate
Successful delivery of analytics or ML solutions with measurable impact on quality, cost, or customer experience. Strong problem-solving skills in ambiguous, data-rich environments. Effective collaboration within cross-functional teams. Clear, structured communication of technical insights and recommendations. Consistent application of sound statistical reasoning and modeling practices. Basic Qualifications:
Bachelor's Degree required with technical focus (e.g. Data science, Statistics, CS, Physics, Engineering, etc.) 5+ years of total experience in data-oriented advanced analytics/ machine learning 3+ years of intensive experience on Databricks, Palantir, Snowflake Exceptional technical skills with Python/R, SQL for data analysis and experience in ML driven products Knowledge of advanced statistical and ML algorithms, experience in Root Cause Analysis is desirable Experience with distributed analytical processing technologies based on Spark Expert at deriving narrative from data and communicate the results effectively Comprehensive experience with predictive and prescriptive modeling/ machine learning Preferred
Qualifications:
Exposure to LLM-based techniques (e.g., RAG, fine-tuning) applied to engineering or analytics problems. Understanding of ASPICE or similar development lifecycle standards. Experience in automotive, manufacturing, or quality-focused analytics environments.
Sprachkenntnisse
- English
Hinweis für Nutzer
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