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The Data Scientist - AI Execution is responsible for designing, building, and iterating AI and machinelearning solutions that power Purchasing data products and automation use cases.
Working within Product Owner-led teams, this role enables datadriven decisioning and intelligent automation while operating within established governance, process, and delivery frameworks. The role ensures that AI capabilities are robust, explainable, and scalable, without fragmenting product ownership or duplicating governance and delivery responsibilities. Key Accountabilities include but not limited to:
- Design and implement AI/ML models aligned to Purchasing use cases (e.g., recommendations, scoring, prediction, classification)
- Partner with Product Owners to translate business needs into executable model logic and expected outcomes
- Collaborate with Data Engineers to ensure models are productionready, scalable, and performant
- Work closely with Data Analysts, FrontEnd Developers, and UI/UX roles to integrate AI outputs into userfacing experiences, including dashboards, chatbots, and AIassisted workflows
- Support multiple AI interaction patterns, including embedded intelligence, conversational interfaces, and emerging agentic and agenttoagent solutions
- Validate model outcomes, explainability, and performance, supporting responsible AI practices
- Contribute to AI reuse, standardization, and patterns across Purchasing initiatives
Basic Qualifications:
- Bachelor of Science degree in Business, Business Administration, Supply Chain Management, Finance, Marketing, Economics, International Business, Accounting, Entrepreneurship, Engineering, or equivalent; Other technical degrees with business background also considered
- 10+ years of experience in the automotive industry or IT.
- Strong English verbal and written communication skills
- Ability to manage multiple services or initiatives with varying complexity
- Proficiency with Microsoft PowerPoint, Excel, and Word
- Ability to work effectively across global teams and organizational levels
- Proven ability to lead cross-functional teams and drive purchasing strategies in a fast-paced environment
- Strong negotiation, analytical, and problem-solving skills
- Highly proactive and visionary, with a track record of driving innovation and continuous improvement
- Ability to communicate effectively with international teams and suppliers
The Data Scientist - AI Execution is responsible for designing, building, and iterating AI and machinelearning solutions that power Purchasing data products and automation use cases.
Working within Product Owner-led teams, this role enables datadriven decisioning and intelligent automation while operating within established governance, process, and delivery frameworks. The role ensures that AI capabilities are robust, explainable, and scalable, without fragmenting product ownership or duplicating governance and delivery responsibilities. Key Accountabilities include but not limited to:
- Design and implement AI/ML models aligned to Purchasing use cases (e.g., recommendations, scoring, prediction, classification)
- Partner with Product Owners to translate business needs into executable model logic and expected outcomes
- Collaborate with Data Engineers to ensure models are productionready, scalable, and performant
- Work closely with Data Analysts, FrontEnd Developers, and UI/UX roles to integrate AI outputs into userfacing experiences, including dashboards, chatbots, and AIassisted workflows
- Support multiple AI interaction patterns, including embedded intelligence, conversational interfaces, and emerging agentic and agenttoagent solutions
- Validate model outcomes, explainability, and performance, supporting responsible AI practices
- Contribute to AI reuse, standardization, and patterns across Purchasing initiatives
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.
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