Global Demand Expert & Data Scientist
At a glance
Mid-level Data Science role at TE Connectivity. Bangalore.
Pay not stated Data Scientist salary
dataroles summary, based on the employer's posting.
What you'll do
- Set the technical direction for AI initiatives in global demand management and SAP IBP
- Build AI and SAP IBP systems for forecasting, data connections, model release and ongoing monitoring
- Develop forecasting, segmentation and anomaly-detection models, then assess their effect on forecast accuracy and planning decisions
- Connect AI tools to SAP IBP planning data and workflows, with explanations and controls that keep planners involved
- Set practices for responsible AI, including governance, explainability, validation, documentation and monitoring
What you bring
- A master’s degree in computer science, data science, machine learning, statistics or a related discipline
- At least six years applying machine learning, deep learning, natural language processing or related methods
- Strong Python skills, familiarity with major ML frameworks and data pipelines, plus practical SAP IBP for Demand knowledge
- Knowledge of demand forecasting and time-series methods, including forecast accuracy, bias, exceptions and scenario analysis
Who this fits
This role suits someone who can combine machine learning expertise with hands-on SAP IBP demand-planning work. You’ll need to turn demand-management needs into deployable solutions and support stakeholder alignment and adoption. The role is based in Bangalore, India.
From the employer
At TE, you will unleash your potential working with people from diverse backgrounds and industries to create a safer, sustainable and more connected world.
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
Values: Integrity, Accountability, Inclusion, Innovation, TeamworkABOUT 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.
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