Basic Qualifications:

Master's degree in data science, statistics, computer science or related field8+ years of professional experience, including 2+ years in supply chain analytics (planning, forecasting, logistics, manufacturing, or operations)Strong proficiency in Python and SQLProven experience with predictive modeling (statistical, ML, deep learning), optimization techniques (LP, MIP, constraint programming), and simulation techniques (Monte Carlo, discrete event)Knowledge of advanced statistical techniques and concepts (regression, distributions, statistical tests)Familiarity with a variety of machine learning techniques (clustering, decision trees, neural networks) and their real-world advantages and limitationsExperience with data manipulation libraries such as pandas and NumPyExperience with ML frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlowKnowledge of big data frameworks and platforms such as

Spark, Databricks, or SnowflakePreferred Qualifications:

PhDExperience with supply chain planning, forecasting, or logistics datasetsExperience with Databricks, Spark, Snowflake or Palantir Foundry & AIPExperience with MLOps practices (model monitoring, CI/CD for ML)We're building an AI-enabled supply chain that predicts, prescribes, and acts. As a Supply Chain Data Scientist, you'll develop predictive, prescriptive, optimization, anomaly detection, and simulation models that improve cost, service, and resilience across planning, logistics, and operations. You will partner with data engineering, AI engineering, and business stakeholders to translate problems into deployable solutions-delivering decision signals that are embedded into operational workflows, planning systems, and agentic experiences.

Responsibilities include but not limited to:

Build predictive models for key supply chain processes using statistical, machine learning, and deep learning techniquesDevelop prescriptive analytics and optimization models to recommend optimal actions under real-world constraintsQuantify tradeoffs between cost, service, capacity, and riskDetect variability, disruptions, and anomalies across supply chain operationsBuild simulations and scenario models to support strategic and operational decisionsPartner with stakeholders to translate business problems into data science solutionsEnable AI and agentic workflows by producing high-quality predictive and prescriptive signalsMerge and analyze large, complex datasets to discover trends, patterns, and actionable insightsAt 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. 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