Data Modeler

Role & responsibilities AgentOrchestrated EndtoEnd Planning : Enable autonomous, crossfunctional supply chain planning that synchronizes demand, supply, manufacturing, and fulfillment to customer outcomes. Autonomous Performance & Loss Management : Deploy AI agents to continuously monitor service, cost, and fulfillment signals, proactively eradicating losses and improving plan adherence. Intelligent Manufacturing & Capacity Optimization : Use agentic insights to analyze production constraints, expedite plans, optimize capacity utilization, and ensure on time production performance. RealTime Disruption Response : Leverage AI to sense and respond to internal and external disruptions by dynamically rerouting logistics and rebalancing inventory to mitigate risk. GoalDriven Inventory & Replenishment : Shift from rulebased planning to autonomous, goalbased replenishment driven by forecasted demand, sales trends, service levels, and costtoserve. Agentic Procurement, Analytics & Data Foundation : Implement intelligent agents for sourcing and contract monitoring, enable agentassisted RCA and decision intelligence, and ensure highquality data integration across enterprise systems Required Qualifications: Experience with AI-driven supply chain platforms (e.g., Resilinc, Databricks, SAP Joule). Strong understanding of end-to-end supply chain (S&P, Logistics, Fulfillment). Experience in managing AI agents, machine learning, or autonomous systems. Knowledge of Python, SQL, or RPA tools is a plus.