AI-Driven After-Sales Logistics Operations Lead

Job Summary:

We are seeking an experienced AI & ML professional with a strong understanding of spare parts warehouse operations to design, develop, and implement machine learning models that enhance forecasting accuracy, inventory optimization, demand prediction, and operational efficiency.

The ideal candidate will bridge domain knowledge in automotive aftersales logistics with technical expertise in AI, ML, and data analytics, driving digital transformation initiatives in warehouse and supply chain management.

Key Responsibilities:

• 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.

Required Qualifications:

• Bachelors or Masters degree in Computer Science, Information Systems, Business, or a related field.
• 7+ years of overall experience, including 3+ years working with Microsoft Power BI, Power Automate and Power Platform.
• Strong knowledge of Power BI, Power Automate, Power Apps, and integration with Microsoft 365,Dynamics 365 and Microsoft Azure tools.
• 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.

Preferred Qualifications:

• Microsoft Certified: Power Platform Fundamentals or Power Platform Solution Architect.
• Experience in process mining tools (e.g., Celonis, Signavio) or RPA tools (e.g., Power Automate Desktop, UIPath, Automation Anywhere).
• Experience in change management and enterprise transformation programs.
• Background in consulting, IT services, or shared service environments is a plus.

Technical Skills:

• Strong proficiency in Python, SQL, and ML libraries (TensorFlow, PyTorch, Scikit-learn).
• Hands-on experience with data wrangling and feature engineering from ERP/WMS datasets.
• Knowledge of predictive modeling, time-series forecasting, and optimization algorithms.
• Familiarity with LLMs and NLP frameworks (e.g., Hugging Face, LangChain, OpenAI API) is a plus.
• Experience integrating AI models with Power BI dashboards or warehouse automation systems.

Domain Knowledge:

• 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.

Soft Skills:

• Strong analytical mindset with problem-solving orientation.
• Excellent communication and stakeholder management skills.
• Ability to work in cross-functional and multi-geography environments.