Lead planning efforts to apply AI for process improvement. Own the 12–24 month roadmap for planning automation, augmentation, or acceleration with AI. Take use cases from PoC to production. Decide when to build or use vendor AI like Kinaxis Maestro, SAP Joule, or Blue Yonder. Measure success by forecast accuracy, plan stability, cycle time, inventory, and manual effort.
Keep Pace with AI: Maintain an AI technology radar, run fast experiments, and set governance for evaluation, explainability, and cost.
Partner with Executives and Lead Change: Be the primary link between Supply Chain leadership, Business Unit's leaders, IT Enterprise AI, and EPS, and present results as business outcomes. Drive adoption with users worldwide by building trust in AI-assisted decisions.
Build the Team: Lead a hybrid group of Industry Analysts, Data Scientists, and Solution Architects, and earn the trust of an EPS team with deep SAP, Kinaxis, and Blue Yonder expertise. Encourage a culture where every initiative owns its business metric, applying Agile delivery.
Minimum Qualifications
Over 12 years of expertise in supply chain planning, planning systems, or planning transformation, including more than 5 years managing teams (technical or combined business/technical).
Comprehensive, hands-on IBP / S&OP / Master Planning knowledge. You have established, handled, or supported a monthly IBP cycle. You can explain demand and supply coordination, constrained against unconstrained planning, allocation, and order scheduling (ATP/CTP) effectively.
Led the implementation or major evolution of at least one advanced planning platform, such as Kinaxis, SAP IBP/APO, Blue Yonder, o9, or an equivalent. This included integrating it with ERP and enterprise data platforms.
Proven delivery of analytics, ML, or GenAI into production planning use, with measurable business outcomes.
Working proficiency in modern AI: LLMs, agentic workflows, retrieval-augmented generation, and model/agent evaluation. You should know enough to challenge architects and data scientists on build choices.
Bachelor’s degree or equivalent experience in Supply Chain, Engineering, Computer Science, Operations Research, or a related area. Candidates with an advanced degree (MS/MBA) will be considered favorably.
Preferred Qualifications
Semiconductor or high-tech planning experience: long lead times, multi-echelon supply, die/bin/product hierarchies, allocation under constraint.
Experience in multi-platform planning landscapes (two or more planning tools coexisting).
Familiarity with Snowflake, semantic layers, and data-product operating models.
Hands-on exposure to enterprise AI tooling: LLM platforms, Microsoft Copilot, agent frameworks, and tool-interoperability standards.
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