Sr. Staff Data Scientist - Machine Learning & AI (Quality, Vehicle & Engineering Analytics)

About the Role:We are looking for a Senior Staff Data Scientist (ML/AI) to serve as a technical leader, architect, and individual contributor within the Machine Learning & AI Engineering team at Stellantis.This role sits at the intersection of machine learning, advanced analytics, experimentation, and large-scale vehicle/IoT data systems. You will define and influence how ML and AI are used across vehicle quality, engineering systems, and customer experience outcomes.This is a high-impact, senior IC role (Staff/Principal level influence) responsible for shaping technical strategy, designing scalable ML systems, and driving measurable business outcomes such as quality improvement, warranty reduction, and customer experience enhancement.What You Will Do:Technical Leadership & ML Strategy (Staff-Level Ownership)Define and evolve the ML/AI architecture and framework supporting quality, engineering, and vehicle analytics across the organizationSet technical direction for:Machine learning systemsExperimentation platformsData science architectureAct as a trusted technical advisor to senior leadership on:Model feasibilityTrade-offs (accuracy, scalability, cost, interpretability)Business impact of ML/AI initiativesInfluence roadmap decisions across engineering and product organizationsAdvanced Machine Learning & Statistical ModelingDevelop and deploy predictive, prescriptive, and causal models using:Vehicle dataIoT sensor dataEnterprise datasetsApply advanced techniques including:Statistical modelingMachine learning algorithmsDeep learning / neural networksLead root cause analysis for vehicle quality, performance, and system failuresDesign and build LLM-based systems and agentic AI solutions for engineering and quality use casesData Science Platform & Scalable SystemsArchitect and guide development of large-scale distributed data and ML systemsBuild and scale analytics pipelines using Spark-based distributed processing frameworksLead ML model lifecycle management, including:TrainingValidationDeploymentMonitoring in productionEnsure models and systems are:ExplainableReliableProduction-readyCompliant with automotive/regulatory standardsExperimentation & Product ImpactOwn and evolve the experimentation framework/platform for safe, scalable testing of vehicle and software featuresDesign statistically sound experiments (A/B tests and beyond)Translate experimental results into clear product and engineering decisionsDrive measurable business outcomes including:Warranty cost reductionImproved product qualityEnhanced customer experienceRevenue-impacting insightsInfluence, Mentorship & Knowledge SharingMentor senior and mid-level data scientists, raising technical standards across the teamHelp teams with:Problem formulationResearch designStatistical interpretationContribute to internal knowledge systems and external-facing technical content (e.g., blogs or papers)Serve as a cross-functional leader bridging engineering, product, and executive teamsWhat Success Looks Like (Top Performers)Strong candidates will demonstrate:Proven impact from deployed ML systems or production analytics productsQuantifiable improvements in:Vehicle qualityWarranty reductionCustomer experience metricsAbility to influence technical strategy beyond their immediate teamStrong communication skills with executive and non-technical stakeholdersDemonstrated ability to turn complex analysis into business decisions and outcomesBasic Qualifications:Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, or a related fieldA minimum of 8 years of experience in data science, advanced analytics, or machine learning, including a minimum of 5 years of hands-on experience with Databricks, Palantir, Snowflake, or AWS SageMakerExpert-level proficiency in:Python (or R)SQLStrong foundation in:Machine learning algorithmsStatistical modelingNeural networks / deep learningExperience building ML solutions on distributed systems (e.g., Spark)Preferred Qualifications:Master’s degree in Computer Science, Computer Engineering, Electrical Engineering, or a related fieldExperience with:Large Language Models (LLMs)Fine-tuning foundation modelsAgentic AI systemsExperience building ML solutions in engineering, automotive, propulsion, or battery systemsStrong understanding of vehicle quality (QA), reliability, or manufacturing analyticsExperience working in high-scale enterprise or regulated environmentsBrand: FCA GroupJob ID: 2019050Employment Type: Full-timeJob Area: ICT, Digital and DataPosted Date: 17/06/2026