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 techniques
- Develop prescriptive analytics and optimization models to recommend optimal actions under real-world constraints
- Quantify tradeoffs between cost, service, capacity, and risk
- Detect variability, disruptions, and anomalies across supply chain operations
- Build simulations and scenario models to support strategic and operational decisions
- Partner with stakeholders to translate business problems into data science solutions
- Enable AI and agentic workflows by producing high-quality predictive and prescriptive signals
- Merge and analyze large, complex datasets to discover trends, patterns, and actionable insights
Basic Qualifications:
- Master’s degree in data science, statistics, computer science or related field
- 8+ years of professional experience, including 2+ years in supply chain analytics (planning, forecasting, logistics, manufacturing, or operations)
- Strong proficiency in Python and SQL
- Proven 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 limitations
- Experience with data manipulation libraries such as pandas and NumPy
- Experience with ML frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow
- Knowledge of big data frameworks and platforms such as Spark, Databricks, or Snowflake
Preferred Qualifications:
- PhD
- Experience with supply chain planning, forecasting, or logistics datasets
- Experience with Databricks, Spark, Snowflake or Palantir Foundry & AIP
- Experience with MLOps practices (model monitoring, CI/CD for ML)
Skills Required
- Master's degree in data science, statistics, computer science or related field
- 8+ years of professional experience
- 2+ years in supply chain analytics
- Strong proficiency in Python and SQL
- Experience with predictive modeling techniques
- Knowledge of advanced statistical techniques and concepts
- Experience with data manipulation libraries
- Experience with machine learning frameworks
- Knowledge of big data frameworks and platforms
Stellantis Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Stellantis and has not been reviewed or approved by Stellantis.
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Pay Growth & Progression — Contract-driven increases lifted hourly wages roughly 25% over 4.5 years and restored cost-of-living adjustments, pushing top rates near $42 per hour by the end of the agreement. Union hourly positions appear to have benefited most since the 2023 deal.
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Affordable Benefits — UAW-represented hourly workers pay no premiums and about 3% of total healthcare costs while receiving comprehensive medical, dental, vision, and wellness coverage. This creates materially lower out-of-pocket costs for represented hourly roles.
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Retirement Support — Post-2007 hourly hires receive a 10% employer 401(k) contribution and legacy workers saw defined-benefit improvements with retiree bonuses. Salaried roles also cite a 401(k) with employer match and contribution up to a maximum of 8%.
Stellantis Insights
What We Do
Our storied and iconic brands embody the passion of their visionary founders and today’s customers in their innovative products and services: they include Abarth, Alfa Romeo, Chrysler, Citroën, Dodge, DS Automobiles, Fiat, Jeep®, Lancia, Maserati, Opel, Peugeot, Ram, Vauxhall and mobility brands Free2move and Leasys. Powered by our diversity, we lead the way the world moves – aspiring to become the greatest sustainable mobility tech company, not the biggest, while creating added value for all stakeholders as well as the communities in which we operate.
