- 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.
- Robust 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

Values: Integrity, Accountability, Inclusion, Innovation, Teamwork

ABOUT TE CONNECTIVITY

TE Connectivity plc (NYSE: TEL) is a global industrial technology leader creating a safer, sustainable, productive, and connected future. As a trusted innovation partner, our broad range of connectivity and sensor solutions enable the distribution of power, signal and data to advance next-generation transportation, energy networks, automated factories, data centers enabling artificial intelligence, and more.

Job Locations:

Doraisanipalya, J.P Nagar, 4th Phase, Bannerghatta Road

Bangalore, Karnātaka 560076

India

Posting City: Bangalore

Job Country: India

Travel Required: Less than 10%

Requisition ID: 159081

Workplace Type: Onsite

External Careers Page: Information Technology

📌 Global Demand Expert & Data Scientist (Bengaluru)
🏢 TE Connectivity
📍 Bengaluru