AI-Driven After-Sales Logistics Operations (Data & Analytics)

Role Overview: You will be responsible for leading AI-driven after-sales logistics operations focusing on data analytics. Your main tasks will involve designing, developing, and implementing machine learning models to enhance forecasting accuracy, inventory optimization, demand prediction, and operational efficiency in spare parts warehouse operations. Key Responsibilities: - Develop and deploy machine learning models for spare parts demand forecasting, inventory optimization, predictive replenishment, stock-out prevention, supplier lead-time analysis, order pattern analysis, and anomaly detection. - Utilize AI techniques like NLP, computer vision, and LLMs for automated parts identification, semantic search in parts catalogs, and intelligent chatbot assistants. - Analyze operational data to identify process bottlenecks and recommend data-driven improvements. - Collaborate with cross-functional teams to implement scalable AI solutions, integrate data pipelines from ERP/WMS systems, prepare dashboards using tools like Power BI or Tableau, and research AI-driven automation tools for spare parts logistics. - Design and deploy automation scripts using Python, SQL, or RPA tools to enhance efficiency in warehouse management. Qualification Required: - Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Information Systems, Business, or related field. - 7+ years of experience with at least 3 years specializing in Artificial Intelligence/Machine Learning development and working with Microsoft Power Platform. - Hands-on experience with chatbots/AI assistants, automation scripts, Power BI, Python, ML libraries, LLMs, NLP frameworks, and agile project lifecycles. - Proficiency in stakeholder communication, risk management, and governance frameworks. - Preferred qualifications include Microsoft Power Platform certification, experience with process mining, and change management. - Strong technical knowledge in integrating AI models, SQL data pipelines, BI dashboards, and warehouse automation systems. - In-depth understanding of spare parts logistics, warehouse operations, SKU segmentation, inventory control, lead-time management, safety stock strategies, and warehouse performance KPIs. Company Details: Omitted as no additional details of the company are mentioned in the JD.,