Machine learning & external sensing engineer
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Role details
Tech stack
Job description
As a Machine Learning & External Sensing Engineer, you will develop Machine Learning, AI-agent, and external sensing capabilities focused on predictive forecasting, intelligent automation, and integration of external business signals into Supply Chain decision-making processes.
How You’ll Spend Your Day
- 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
Requirements
- 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, * Experience with Pharma datasets
- Exposure to AI agents / LLM-based automation
- Experience working with SAP planning ecosystems
- Experience with external sensing, signal detection, or predictive analytics environments
About the company
We’re Teva, a leading innovative biopharmaceutical company, enabled by a world-class generics business. Whether it’s innovating in the fields of neuroscience and immunology or delivering high-quality medicine worldwide, we’re dedicated to addressing patients’ needs now and in the future. Here, you will be part of a high-performing, inclusive culture that values fresh thinking and collaboration. You’ll have the room to grow, the flexibility to balance life with work, and the opportunity to better health worldwide, together.
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