Senior Data Scientist - Supply Chain

Stellantis
United States, Michigan, Auburn Hills
May 02, 2026
We are building an AI-enabled supply chain that senses, predicts, prescribes, and acts. As a Senior Data Scientist, you will architect and deliver advanced analytical solutions that shape how the Supply Chain organization makes decisions. You will lead the development of predictive, prescriptive, optimization, anomaly detection, and simulation models - and ensure they are embedded into real workflows, systems, and AI agents. This role is ideal for someone who can operate at both the strategic and technical levels: designing decision frameworks, influencing cross-functional partners, and building models that materially improve cost, service, and resilience. Responsibilities include but not limited to: Lead the design and development of predictive, prescriptive, and simulation models that support enterprise-level supply chain decisions Architect optimization frameworks that balance cost, service, capacity, and risk under real-world constraints Translate ambiguous business problems into structured analytical approaches and decision models Identify and quantify systemic risks, variability, and anomalies across supply chain operations Build scenario and simulation environments that enable leadership to evaluate strategic tradeoffs and "what-if" conditions Partner with senior stakeholders to define requirements and influence decisionmaking Ensure analytical outputs are integrated into AI agents, planning systems, and operational workflows Mentor other data scientists and elevate analytical standards across the team Drive best practices in data quality, feature engineering, model governance, and performance monitoring Basic Qualifications: Master's degree in data science, statistics, computer science or related field 8+ years of professional experience, including 5+ years in supply chain analytics, optimization, or simulation Proven ability to operate independently, lead analytical workstreams end-to-end, and influence decisions with minimal oversight Strong proficiency in Python and SQL, with the ability to design scalable analytical pipelines Deep experience with predictive modeling (statistical, ML, deep learning), optimization techniques (LP, MIP, constraint programming), and simulation methods (Monte Carlo, discrete event) Strong understanding of supply chain processes and the analytical levers that influence cost, service, and resilience Experience designing decision frameworks and translating them into optimization or prescriptive models Familiarity with machine learning techniques (clustering, tree-based models, neural networks) and their practical tradeoffs Experience with data manipulation libraries (pandas, NumPy) and ML frameworks (scikit-learn, XGBoost, PyTorch, TensorFlow) Experience with big data platforms such as Spark, Databricks, or Snowflake Ability to communicate complex analytical concepts to senior leaders in clear, business-focused language Experience mentoring or leading technical contributors is a plus Preferred Qualifications: PhD Experience designing optimization or simulation models for supply chain decisions Background in stochastic modeling, network optimization, or discrete-event simulation Experience embedding predictive or prescriptive models into operational systems Strong executive communication skills and experience influencing senior stakeholders We are building an AI-enabled supply chain that senses, predicts, prescribes, and acts. As a Senior Data Scientist, you will architect and deliver advanced analytical solutions that shape how the Supply Chain organization makes decisions. You will lead the development of predictive, prescriptive, optimization, anomaly detection, and simulation models - and ensure they are embedded into real workflows, systems, and AI agents. This role is ideal for someone who can operate at both the strategic and technical levels: designing decision frameworks, influencing cross-functional partners, and building models that materially improve cost, service, and resilience. Responsibilities include but not limited to: Lead the design and development of predictive, prescriptive, and simulation models that support enterprise-level supply chain decisions Architect optimization frameworks that balance cost, service, capacity, and risk under real-world constraints Translate ambiguous business problems into structured analytical approaches and decision models Identify and quantify systemic risks, variability, and anomalies across supply chain operations Build scenario and simulation environments that enable leadership to evaluate strategic tradeoffs and "what-if" conditions Partner with senior stakeholders to define requirements and influence decisionmaking Ensure analytical outputs are integrated into AI agents, planning systems, and operational workflows Mentor other data scientists and elevate analytical standards across the team Drive best practices in data quality, feature engineering, model governance, and performance monitoring At Stellantis, we assess candidates based on qualifications, merit, and business needs. We welcome applications from all people without regard to sex, age, ethnicity, nationality, religion, sexual orientation, disability, or any characteristic protected by law. We believe that diverse teams reflect our identity as a global company, enabling us to better address the evolving needs of our customers and care for our future.