The Global Stellantis Quality organization is seeking a highly analytical and proactive Field Quality Monitoring & Early Warning Analyst to join the Global Field Quality Monitoring & Early Warning team. The overall objective is to support the detection, assessment, and escalation of emerging field quality risks through the application of early-monitoring KPIs, triggers, and analytical tools, enabling the organization to identify potential quality issues before they result in significant customer impact and warranty cost.
Key Responsibilities:
Deliverables of the function include on-time and effective delivery of:
- Monitor early field quality indicators and KPIs to identify emerging quality, warranty, durability, and customer-impact risks across multiple models and systems
- Assess and validate potential risks by applying defined monitoring criteria, severity thresholds, and analytical methods to distinguish meaningful signals from normal variation
- Prioritize and manage the early-warning pipeline, maintaining dashboards and risk summaries while determining which issues require continued monitoring, technical investigation, or escalation.
- Support early-warning governance and technical review forums by preparing analyses, facilitating issue reviews, tracking actions, and ensuring timely follow-up on identified risks.
Support continuous improvement of monitoring tools, KPIs, triggers, and processes to improve detection effectiveness, reporting quality, and early intervention capability.
Basic Qualifications:
- Bachelor's degree in Engineering, Data Analytics or a related technical discipline
- 7+ years of experience in quality, engineering, manufacturing or analytics
- Experience in automotive field quality, warranty analysis, reliability engineering, or related technical disciplines
- Strong analytical skills with the ability to identify trends, anomalies, and emerging risks within large and complex datasets
- Experience translating data into clear conclusions and actionable recommendations
- Strong communication skills with the ability to present fact-based analyses to technical and business stakeholders
Preferred Qualifications:
- Experience with warranty, reliability, durability, or field quality monitoring systems
- Hands-on experience with Palantir Foundry
- Knowledge of statistical analysis, trend analysis, and anomaly detection techniques
- Advanced degree in Business, Engineering, Data Science or related field