Quality Data Scientist - Electrical Systems & Field Quality Engineering

Stellantis Financial Services; Auburn Hills (MI); On-site; USD 120,000 - 160,000; Full time

Job summary

Stellantis Financial Services in North America seeks a strategic Data Scientist to support Warranty Analytics and Programs. You will develop scalable analytics, predictive models, and early‑warning capabilities to detect quality trends across large enterprise datasets.

You will translate complex analyses into executive‑ready PowerPoint presentations, partner with business stakeholders, and deliver insights that drive faster, data‑driven decisions.

Qualifications

• Bachelor’s degree in a quantitative field or related discipline.
• 7+ years of professional data science experience.
• Strong proficiency in Python, SQL, PySpark and data visualization tools.

Responsibilities

• Lead cross‑functional analytics initiatives from problem definition through deployment.
• Build, validate, and deploy predictive models for warranty claims and quality trends.
• Create executive‑level communications and Dashboards to enable data‑driven decisions.
• Monitor model performance and drive improvements.

Skills

Python

SQL

PySpark

Power BI

Palantir Foundry

AWS/Azure/GCP

Machine Learning

Statistical analysis

Communication

Education

Bachelor's degree

Master's degree

Tools

Palantir Foundry

Snowflake

Databricks

AWS

Azure

GCP

Job description

Are you passionate about transforming complex data into actionable insights that improve product quality and customer satisfaction? We are seeking a strategic, hands‑on Data Scientist to support Warranty Analytics and Programs within our North America quality team.

The ideal candidate combines advanced data analytics, predictive modeling, and data manipulation expertise with the ability to communicate complex findings through clear, executive‑ready PowerPoint presentations. You will be part of a talented team developing scalable analytics, predictive models, and early‑warning capabilities to detect emerging quality trends across large enterprise datasets.

This is a fast‑paced environment focused on rapid, high‑quality delivery for business partners. You will work in a highly collaborative organization that values analytical rigor, speed, innovation, and measurable business impact.

Key Responsibilities:

• Lead and coordinate cross‑functional analytics and AI initiatives from problem definition through deployment, ensuring alignment with business objectives, timelines, and measurable outcomes.
• Perform deep exploratory, diagnostic, and predictive analysis to identify patterns, relationships, anomalies, emerging risks, and leading indicators within complex datasets.
• Build, validate, and deploy predictive models to forecast warranty claims, component failure rates, quality trends, repair demand, and cost exposure.
• Apply statistical analysis, machine learning, forecasting, segmentation, and anomaly‑detection techniques to solve business and operational problems.
• Manipulate, integrate, cleanse, transform, and analyze large structured and unstructured datasets from multiple enterprise sources using Python, SQL, PySpark, and related tools.
• Develop robust, repeatable analytical workflows and reusable data products that support scalable decision‑making and consistent results.
• Partner with business stakeholders to define analytical questions, translate business needs into actionable use cases and technical requirements, and establish success criteria.
• Collaborate with data scientists, data engineers, platform teams, and subject‑matter experts to improve data accessibility, model performance, scalability, and adoption.
• Create compelling, executive‑ready PowerPoint presentations that clearly communicate analytical methods, findings, predictions, business implications, risks, recommendations, and next steps.
• Develop dashboards, visualizations, and analytical outputs that enable insight adoption, operational action, and performance monitoring.
• Present complex analytical findings to technical and nontechnical audiences using concise storytelling, strong visual design, and decision‑focused recommendations.
• Ensure data quality, lineage, documentation, model transparency, and compliance with enterprise governance requirements.
• Monitor model performance and analytical outputs, identify degradation or changing patterns, and recommend model recalibration or process improvements.

Basic Qualifications:

• Bachelor’s degree in Data Science, Statistics, Mathematics, Engineering, Computer Science, Business Analytics, or a related quantitative field
• 7+ years of professional experience as a Data Scientist, Advanced Data Analyst, Predictive Analytics Specialist, or similar role
• Strong proficiency in Python, SQL, PySpark, and data visualization tools such as Power BI or Palantir Foundry Workshop
• Experience working with one or more enterprise data or cloud platforms, such as Palantir Foundry, Snowflake, Databricks, AWS, Azure, or GCP
• Demonstrated experience performing advanced data analysis and developing predictive models that support business or operational decisions
• Advanced data manipulation skills, including data extraction, cleansing, transformation, joining, feature engineering, validation, and analysis of large, complex datasets
• Strong understanding of statistics, exploratory data analysis, hypothesis testing, regression, classification, forecasting, clustering, model evaluation, and applied machine learning
• Proven experience delivering end‑to‑end analytics or data science solutions from requirements gathering and data preparation through validation, deployment, and monitoring
• Advanced proficiency in Microsoft PowerPoint, including development of executive‑level presentations, analytical storytelling, charts, visual summaries, and clear recommendations for senior leadership
• Ability to translate complex analytical findings and model outputs into concise, actionable business insights for technical and nontechnical audiences
• Strong communication, stakeholder engagement, problem‑solving, prioritization, and cross‑functional collaboration skills

Preferred Qualifications:

• Master’s degree in Data Science, Statistics, Mathematics, Engineering, Computer Science, Business Analytics, or a related quantitative field
• Extensive experience in deep data analysis, predictive analytics, forecasting, and development of models that identify future risks, trends, or outcomes
• Demonstrated success converting complex analytical work into persuasive, executive‑ready PowerPoint presentations that support decisions and action
• Industry experience in automotive, warranty, quality, manufacturing, service operations, or related fields
• Familiarity with data modeling, semantic layers, feature stores, and enterprise data platforms
• Experience with MLOps concepts, model deployment, versioning, monitoring, explainability, and governance
• Hands‑on experience with Palantir Foundry, Snowflake Intelligence, Power BI, CoPilot, Anthropic, Gemin, and other forms of OpenAI/GPT or comparable analytics, LLM, and AI platforms
• Experience analyzing unstructured data, including text, service narratives, customer complaints, or technical documentation