This list contains only the countries for which job offers have been published in the selected language (e.g., in the French version, only job offers written in French are displayed, and in the English version, only those in English).
We are seeking an experienced AI & ML professional with deep expertise in spare parts warehouse operations to design, develop, and implement machine learning models that improve forecasting accuracy, inventory optimization, demand prediction, and overall operational efficiency. The ideal candidate will bridge domain knowledge in automotive aftersales logistics with technical expertise in AI, ML, data analytics, and automation tools to enhance efficiency in warehouse/supply chain operations.
Job Responsibility:
Develop and deploy ML models for: Spare parts demand forecasting and inventory optimization
Predictive replenishment and stock-out prevention
Supplier lead-time and order pattern analysis
Anomaly detection for pricing, returns, and demand spikes
Leverage AI techniques (NLP, computer vision, and LLMs) for: Automated parts identification using image recognition
Semantic search across parts catalogs and technical documentation
Intelligent chatbot assistants for warehouse or dealer queries
Analyze operational data (warehouse throughput, order lines, pick/pack times) to identify process bottlenecks and recommend data-driven improvements
Collaborate cross-functionally with warehouse managers, supply chain planners, IT, and digital transformation teams to implement scalable AI solutions
Evaluate and integrate data pipelines from ERP/WMS systems (SAP, Oracle, or similar) for continuous model improvement and monitoring
Prepare dashboards and visualizations using tools like Power BI or Tableau to present insights and recommendations to leadership teams
Research and pilot AI-driven automation tools to improve efficiency in spare parts logistics and warehouse management
Design and deploy automation scripts using Python, SQL, or RPA tools to eliminate manual processes and enhance system integration efficiency
Requirements:
Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Information Systems, Business, or a related field
7+ years of overall experience, including at least 3 years specializing in Artificial Intelligence/Machine Learning development and working with Microsoft Power Platform (Power Automate, Power BI, Power Apps)
Proven experience in designing and developing chatbots/AI assistants integrated with databases for user interaction and process automation
Hands-on experience creating automation scripts or workflows to optimize manual data processes using tools such as Python (Pandas, OpenPyXL), Power Automate, or UiPath
Strong knowledge of Power BI, Power Automate, Power Apps, and integration with Microsoft 365, Dynamics 365 and Microsoft Azure tools
Strong proficiency in Python, with experience using ML libraries such as TensorFlow, PyTorch, and Scikit-learn
Experience managing agile, hybrid, or waterfall project lifecycles
Proficient in stakeholder communication, risk management, and reporting at executive levels
Familiarity with governance, Center of Excellence (CoE) frameworks, and scalable solution design
In-depth understanding of spare parts logistics, warehouse operations, and aftersales supply chains
Experience in SKU segmentation, ABC analysis, and inventory control principles
Familiarity with lead-time management, safety stock strategies, and warehouse performance KPIs
Nice to have:
Microsoft Certified: Power Platform Fundamentals or Power Platform Solution Architect
Experience with process mining (Celonis, Signavio)
Experience in change management and enterprise transformation programs
Proven Experience with LLMs and NLP frameworks (Hugging Face, LangChain, OpenAI API)