Staff Data Scientist

Stellantis • Auburn Hills, MI

4d

About The Position

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.

Requirements

• 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

Nice To Haves

• 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.

Responsibilities

• 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.
• 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.
• 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.
• 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level