Process Data Scientist

Holcim, a global leader in sustainable construction, is seeking a Process Data Scientist to join their team in Zug, Switzerland. The company specializes in providing high-value building materials and solutions, focusing on sustainability and innovation across various sectors, including infrastructure, industry, and buildings. Their portfolio includes premium brands like ECOPact, ECOPlanet, ECOCycle, and Ytong. The Process Data Scientist will be responsible for developing and deploying advanced AI applications to enhance operational and energy efficiency in the cement manufacturing process. This includes designing and validating hybrid Machine Learning algorithms, creating predictive models for real-time process variables, and ensuring seamless integration with both legacy and new Plant of Tomorrow technologies. The role involves working on various manufacturing process optimization initiatives, including the flagship solution P-PREDICT. To excel in this role, candidates must have a Master's or PhD in fields such as Computer Science, Chemical Engineering, Data Science, Electrical Engineering, or Systems & Control. Additionally, candidates should have at least three years of experience in applied Machine Learning and Data Science projects focused on heavy industry process optimization. Experience with productizing and scaling ML models in production environments, as well as industrial change management, is also required. Certifications in C3.ai Data Science or equivalent enterprise AI frameworks are advantageous. Nice-to-have skills include experience in industrial change management, coaching, and technical knowledge transfer to ensure full plant adoption of digital control systems. The role is based in Zug, Switzerland, offering a dynamic and innovative work environment with a focus on sustainability and continuous learning. What the role asks for: - Master's or PhD in Computer Science, Chemical Engineering, Data Science, Electrical Engineering, Systems & Control, or equivalent fields. - 3+ years' experience in applied Machine Learning and Data Science projects focused on heavy industry process optimization. - 2+ years' experience productizing and scaling ML models in production environments. - High proficiency in Python (PyTorch, TensorFlow, Scikit-learn, Pandas, NumPy) and R/SQL. - Experience with prototype and production data pipelines. - Practical experience working with modern data platforms, including BigQuery, cloud data warehouses, data lakes, and lakehouse architectures on platforms such as GCP or AWS. - Experience working with time-series databases and industrial data platforms such as InfluxDB and Seeq. - C3.ai Certifications (C3.ai Data Science, C3.ai V8 Data Science/Application Development) or equivalent enterprise AI framework certification (Advantage).