ML & External Sensing Engineer for Supply Chain AI

Iberdrola Group; Madrid; Presencial; EUR 65.000 - 90.000; Jornada completa

Descripción de la vacante

Teva in Madrid is seeking a Machine Learning & External Sensing Engineer to advance predictive forecasting and analytics across Supply Chain. You will develop ML models that integrate external data sources and build AI-enabled forecasting capabilities.

Collaborate with IT to industrialize data pipelines and with cross-functional teams to operationalize external sensing. The role requires 4+ years in ML, strong Python, and time-series and cloud analytics experience; pharma datasets are a plus.

Formación

• 4+ years in Machine Learning / Data Science.
• Strong Python experience.
• Experience with time-series forecasting.
• Experience integrating structured and unstructured external data sources.
• Knowledge of Supply Chain or Demand Planning processes.
• Experience with cloud-based analytics or AI environments.

Responsabilidades

• Develop Machine Learning models integrating external data sources.
• Build forecasting enhancement capabilities using internal and external signals.
• Integrate external indicators into planning and decision-support processes.
• Develop AI agents supporting analytics, simulations, and operational monitoring.
• Support automation of master data integrity and planning consistency checks.
• Develop anomaly-detection and predictive alerting capabilities leveraging external signals.
• Work with IT to industrialize data pipelines and AI services.
• Collaborate with Commercial, Portfolio, Market Intelligence, and Analytics teams to operationalize external sensing capabilities.

Conocimientos

Machine Learning

Python

Time-series forecasting

External data integration

Supply chain / Demand planning

Cloud analytics

Descripción del empleo

Teva in Madrid is seeking a Machine Learning & External Sensing Engineer to advance predictive forecasting and analytics across Supply Chain. You will develop ML models that integrate external data sources and build AI-enabled forecasting capabilities.

Collaborate with IT to industrialize data pipelines and with cross-functional teams to operationalize external sensing. The role requires 4+ years in ML, strong Python, and time-series and cloud analytics experience; pharma datasets are a plus.