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Protocol Intelligence
Data-driven signals on your job's competitivenessMid-level, metro role with moderately strong employer brand but niche SAP IBP and forecasting requirements.
Requires SAP IBP and demand-forecasting expertise, so skills are highly domain-specific and less transferable.
Multiple explicit requirements (6+ years, master's, SAP IBP, ML/MLOps, LLM experience) narrow candidate pool.
Job Description
Structured overview of role & requirementsAbout This Role
Lead technical roadmap and architecture for AI-driven Global Demand Management and SAP IBP solutions focusing on demand forecasting and integration.
Design, deploy, and optimize machine learning models specifically for demand forecasting, segmentation, anomaly detection, and predictive insights within SAP IBP.
Establish governance standards for AI and SAP IBP initiatives ensuring explainability, reproducibility, sustainability, and measure adoption impact on forecast accuracy and planner productivity.
Minimum Requirements
Master’s degree in Computer Science, Data Science, Machine Learning, Statistics, or related field.
6+ years of professional experience in machine learning, deep learning, or applied data science with strong Python and ML/DL framework skills (TensorFlow, PyTorch, Scikit-learn).
Hands-on expertise with SAP IBP for Demand including forecasting, planning data, analytics, and workflow integration.
Experience with demand forecasting techniques including time-series modeling, transformers, RNNs/LSTMs, and knowledge of MLOps, cloud platforms, and AI governance.
Ideal Candidate Profile
Experienced in translating complex demand-management requirements into scalable AI and SAP IBP solutions with measurable business outcomes.
Demonstrates strong technical leadership integrating advanced ML models within SAP IBP environments to improve forecast accuracy and planner decision support.
Deep domain expertise in demand forecasting, time-series analysis, and practical application of responsible AI principles including explainability and validation.