Business Intelligence Data Scientist
Stellantis · Auburn Hills, MI · 2 mo ago
Quality AssuranceFull-time
Key Responsibilities
- Analyze large, complex datasets to identify trends, relationships, risks, and opportunities related to warranty and quality performance
- Develop and apply advanced statistical, analytical, and data science techniques to support business problem-solving and decision-making
- Perform exploratory data analysis and root-cause investigations to explain performance drivers and anomalies
- Design, develop, and maintain robust analytical models, metrics, and methodologies
- Translate complex analytical results into clear insights, recommendations, and visualizations for stakeholders
- Partner with cross-functional teams to understand business needs and deliver analytical solutions
- Ensure analytical outputs are accurate, repeatable, and well-documented
- Support continuous improvement of analytics processes, tools, and data usage practices
- Contribute to the development of standardized reporting, metrics, and best practices across the organization
Basic Qualifications
- Bachelor’s degree in a quantitative discipline such as Data Science, Statistics, Computer Science, Applied Mathematics, or a related field
- Relevant internship experience
- Demonstrated ability to communicate analytical findings clearly to technical and non-technical audiences
- Excellent problem-solving, organizational, and time-management skills
- Ability to work independently with minimal supervision
Preferred Qualifications
- Master’s degree in a quantitative discipline
- Experience applying predictive, diagnostic, or prescriptive analytics techniques in a business environment
- Familiarity with data visualization and business intelligence tools (e.g., Power BI, Tableau)
- Experience working in automotive, manufacturing, quality, or operational analytics environments
- Experience with working across multiple deployment environments including cloud, on-premises and hybrid, using multiple operating systems
- Experience translating complex data into clear narratives for leadership decision-making