Process Data Scientist

Holcim is seeking an innovative Process Data Scientist motivated to solve operational and energy challenges in the construction industry. This role focuses on developing and deploying cutting-edge AI applications to enhance kiln and thermal efficiency, optimize process stability, reduce fuel consumption, drive Alternative Fuel substitution, and curb CO2 emissions across Plants of Tomorrow.

• Design, configure, and validate hybrid Machine Learning algorithms combining process physics and adaptive AI loops for calciner and kiln optimization.
• Develop predictive soft sensors for real-time process variables, such as fuel calorific value forecasting and clinker quality prediction.
• Build multi-variable target recommenders for control loops of kilns and other equipment.
• Use deep learning, time-series forecasting, and probabilistic models to predict operational hazards like ring formation risk, cyclone blockages, and pressure spikes.
• Manage the end-to-end lifecycle of models, including feature engineering, design, cloud/edge deployment, continuous tuning, and automated retraining pipelines.
• Collaborate with vendors on deployment and customization of solutions and development of proprietary solutions.
• Design operational logic, reason codes, and metrics for operator dashboards to ensure explainability and user trust.
• Work closely with process engineers and plant operators to translate operational knowledge into accurate model boundaries.
• Drive global uptake and utilization of P-PREDICT and other initiatives through plant onboarding, commissioning support, and feedback loops.
• Provide coaching, knowhow transfer, and technical documentation for plant process engineers.