Warranty Data Analyst / Data Scientist

StellantisAuburn Hills, MI

About The Position

The company is seeking a strategic and hands-on Data Scientist to support warranty analytics and programs within their North America Quality Team. The ideal candidate is passionate about transforming data into actionable insights to drive product quality and customer satisfaction. This role involves building scalable analytics, models, and data products in enterprise environments, and will be part of a team focused on predictive analytics and early detection of emerging quality trends using vast datasets. The position is in a fast-paced, highly collaborative environment that values speed and quality, with a strong desire to drive change and value for business partners.

Requirements

  • Bachelor’s degree in Data Science, Statistics, Engineering, Computer Science, or related field
  • 5+ years experience as Data Scientist, Advanced Analyst, or similar role
  • Strong proficiency in Python, SQL, PySpark and visualization tools (e.g., Power BI, Foundry Workshop)
  • Solid understanding of statistics, exploratory data analysis, and applied machine learning
  • Experience working with large, complex datasets in enterprise environments
  • Ability to communicate analytical findings clearly to technical and non‑technical audiences
  • Proven experience delivering end‑to‑end analytics or data science solutions into production
  • Experience with one or two data and cloud platforms (e.g., Palantir Foundry. Snowflake, Databricks AWS, Azure, GCP)
  • Strong communication and stakeholder engagement skills

Nice To Haves

  • Familiarity with data modeling, semantic layers, and enterprise data platforms
  • Industry experience in automotive and manufacturing
  • Exposure to MLOps concepts, model deployment, or monitoring
  • Hands-on experience with Palantir Foundry, Snowflake Intelligence
  • Master’s degree in Data Science, Statistics, Engineering, Computer Science, or related field

Responsibilities

  • Lead and coordinate cross-functional AI programs from concept to deployment, ensuring alignment with business goals and timelines
  • Collaborate with other data scientists, engineers, and business stakeholders to define and prioritize program objectives
  • Apply statistical analysis and machine learning techniques to solve business and operational problems
  • Partner with business stakeholders to understand requirements and translate them into analytical solutions
  • Translate business needs into actionable AI use cases and technical requirements
  • Build and deploy predictive models to forecast warranty claims, failure rates, and cost trends
  • Ensure data quality, lineage, documentation, and compliance with governance requirements
  • Create dashboards and analytical outputs that drive insight adoption and operational impact
  • Collaborate with business data engineers, and platform teams on scalability, performance, and best practices
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