We are looking for a Machine Learning Engineer / Data Scientist to develop advanced statistical models and simulations that drive Vehicle Configuration Optimization (VCO). This role will leverage curated datasets to build a customer-level preference simulation engine, enabling optimized vehicle order guides (VOGs) for future model years.
This is a highly impactful role for an early-to-mid career data scientist who enjoys combining statistical rigor, large-scale data, and real-world business impact.
Key Responsibilities:
- Build and run large-scale simulations (e.g., 50,000 synthetic customers) to model vehicle purchase behavior
- Develop statistical and machine learning models using Databricks
- Leverage datasets including:
- Historical vehicle sales
- Competitive sales data
- Feature-level willingness-to-pay data
- Customer preference models
- Translate model outputs into optimized Vehicle Order Guides (VOGs) that inform product configuration decisions
- Perform exploratory data analysis and feature engineering on complex datasets
- Collaborate closely with Data Engineering to refine and leverage curated datasets
- Communicate insights and model recommendations to business stakeholders
- Continuously evaluate and improve model accuracy and assumptions
Basic Qualifications:
- Bachelors Degree Required
- Minimum 5 years of experience in data science, machine learning, or applied statistics
- Strong experience with Databricks (critical requirement)
- Proficiency in Python (Pandas, NumPy, scikit-learn, PySpark)
- Strong SQL skills
- Solid background in statistical modeling, simulation techniques, and experimental design
- Experience translating analytical results into business decisions
Preferred Qualifications:
- Experience with choice modeling, conjoint analysis, or demand modeling
- Background in automotive, pricing, or product optimization analytics
- Experience working with large-scale simulation frameworks
- Familiarity with Spark and distributed computing
- Exposure to MLOps or model productionization
Skills Required
- Bachelor's degree
- Minimum 5 years experience in data science, machine learning, or applied statistics
- Strong experience with Databricks
- Proficiency in Python (Pandas, NumPy, scikit-learn, PySpark)
- Strong SQL skills
- Solid background in statistical modeling, simulation techniques, and experimental design
- Experience translating analytical results into business decisions
- Experience with choice modeling, conjoint analysis, or demand modeling
- Background in automotive, pricing, or product optimization analytics
- Experience working with large-scale simulation frameworks
- Familiarity with Spark and distributed computing
- Exposure to MLOps or model productionization
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.
