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

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.