Job Overview

• Define the technical roadmap for Global Demand Management AI initiatives and SAP IBP capabilities.
• Architect end-to-end AI and SAP IBP solutions supporting demand forecasting, data integration, model deployment, and monitoring.
• Provide technical leadership across demand analytics, AI modeling, experimentation, and SAP IBP solution development.
• Establish standards for AI and SAP IBP governance, explainability, reproducibility, documentation, and sustainable adoption.
• Design and deploy machine learning models for demand forecasting, segmentation, anomaly detection, and predictive insights within SAP IBP.

• Apply feature engineering, model optimization, and MLOps practices to deliver scalable AI solutions supporting Global Demand Management and SAP IBP.
• Evaluate model performance and business impact to improve forecast accuracy, exception management, and demand-planning decisions.
• SAP IBP integration: Connect AI solutions with SAP IBP data, workflows, analytics, and planning processes.

• Demand-specific use cases: Forecast explanations, exception prioritization, demand-driver analysis, scenario recommendations, and planner support.
• Human-in-the-loop controls: Position AI as decision support rather than fully autonomous decision-making.
• Time-series expertise: Retain transformers, RNNs/LSTMs, embeddings, and transfer learning only where relevant to forecasting and demand patterns.
• Responsible AI: Include explainability, validation, security, governance, and monitoring.
• Adoption and value: Measure improvement in forecast accuracy, planner productivity, exception resolution, and decision quality.

What your background should look like:

• Master’s in Computer Science, Data Science, Machine Learning, Statistics, or related field.
• 6+ years of experience in machine learning, deep learning, natural language processing, or applied Strong proficiency in Python, ML/DL frameworks (TensorFlow, PyTorch, Scikit-learn), and data pipelines.

• Hands-on knowledge of SAP IBP for Demand, planning data, forecasting processes, analytics, and workflow integration.
• Strong understanding of demand forecasting, time-series modeling, segmentation, forecast accuracy, bias, exceptions, and scenario analysis.
• Experience with LLMs, Generative AI, Agentic AI, vector databases, RAG pipelines, and model evaluation and fine-tuning.
• Experience with transformers, RNNs/LSTMs, embeddings, transfer learning, and predictive modeling for demand and time-series use cases.
• Familiarity with MLOps, cloud platforms, and big-data ecosystems, including model deployment, monitoring, governance, and security.
• Ability to translate demand-management requirements into scalable AI and SAP IBP solutions and drive stakeholder alignment, adoption, and measurable business value.

Competencies