Process Data Scientist / Process Data Scientistess

Join Holcim – Your Partner for Sustainable Construction

Holcim is the premier partner for sustainable construction, boasting net sales of CHF 15.7 billion in 2025. We create value across the built environment, spanning infrastructure and industry to buildings. Headquartered in Zug, Switzerland, Holcim employs over 50,000 staff across 45 countries, including regions in Europe, Latin America, and Asia, the Middle East, and Africa. We have been recognized as a Global Top Employer by the Top Employers Institute.

Holcim offers high-value end-to-end Building Materials and Building Solutions, from foundations and flooring to walling and roofing—powered by premium brands such as ECOPact, ECOPlanet, ECOCycle, and Ytong.

Role Overview

As we strive for more sustainable methods of construction, we are seeking world-class talent to join our team. We are looking for individuals who are passionate about sustainability, driven by curiosity, and eager to learn and grow within our high-performance culture.

We are currently in search of an innovative Process Data Scientist who is motivated to tackle significant operational and energy challenges within our industry. This role aims to develop and deploy advanced AI applications that enhance kiln and thermal efficiency. The Process Data Scientist will leverage digital tools to optimize process stability, reduce fuel consumption, drive the substitution of Alternative Fuels, and minimize CO2 emissions across our Plants of Tomorrow.

Main Responsibilities

• Machine Learning & Physics-AI Hybrid Model Design, Tuning, and Validation:
  • Design, configure, and validate hybrid Machine Learning algorithms integrating first-principles process physics and adaptive AI loops for calciner and kiln optimization.
  • Develop predictive soft sensors for real-time process variables, such as forecasting the calorific value of alternative fuels and predicting clinker quality.
  • Build multi-variable target recommenders for control loops of our kilns and other equipment.
  • Employ deep learning, time-series forecasting, and probabilistic models to predict operational hazards (e.g., ring formation risk, cyclone blockages, and pressure spikes).
• Model Lifecycle Management:
  • Manage the complete lifecycle of models, including feature engineering, design, cloud/edge deployment, continuous tuning, and automated retraining pipelines.
  • Collaborate with vendors on the deployment and customization of solutions and development of Holcim proprietary solutions.
• Explainable AI (XAI) & Operator Interface Integration:
  • Design operational logic, reason codes, and metrics for display on operator dashboards to ensure high explainability and user trust.
  • Work closely with process engineers and plant operators to convert operational knowledge into precise model boundaries.
• Field Adoption & Knowledge Transfer:
  • Drive global adoption and utilization of P-PREDICT and other Plant of Tomorrow (PoT) initiatives through structured onboarding, commissioning support, and feedback loops.
  • Provide coaching, knowledge transfer, and technical documentation for plant process engineers.

Your Profile

• Education: MS or PhD in Computer Science, Chemical Engineering, Data Science, Electrical Engineering, Systems & Control, or equivalent fields. C3.ai Certifications (C3.ai Data Science, C3.ai V8 Data Science/Application Development) or equivalent enterprise AI framework certification is a plus.
• Experience:
  • 3+ years in applied Machine Learning and Data Science projects focused on heavy industry process optimization (cement, chemical, energy, or mineral processing preferred).
  • 2+ years productizing and scaling ML models in production environments (both Cloud and EDGE).
  • 2+ years in industrial change management, coaching, and technical knowledge transfer to ensure full plant adoption of digital control systems (advantageous).
• Technical Competencies:
  • Applied Machine Learning expertise in anomaly detection, time-series forecasting, regression analysis, and both supervised and unsupervised learning.
  • Strong mathematical and domain knowledge in linear algebra, calculus, probability/statistics, and basic process control dynamics.
  • High proficiency in programming (particularly Python and R/SQL) and experience with data pipeline development.
  • Experience with data warehousing, lakes, and scalable systems, including knowledge of modern platforms like BigQuery, GCP, and AWS.
  • Familiarity with time-series databases, data engineering practices, and data visualization tools.
  • Experience deploying and monitoring machine-learning solutions in cloud environments, including familiarity with MLOps practices.

Benefits

• Hybrid work contract
• Family Support: Subsidized childcare and paid maternity/paternity leave
• Professional Growth: Company-sponsored training and development opportunities
• Discounts and Perks: Subsidized meals, exclusive discounts, and company gifts for special occasions
• Long-service awards
• Employee referral bonus
• Pension and Savings: Access to a comprehensive pension fund and an employee savings scheme

Holcim is dedicated to fostering a diverse and inclusive workplace. We uphold equal opportunities for all individuals, irrespective of race, national origin, gender, sexuality, disability, or age.

Apply online using the form below. Please note that only applications matching the job profile will be considered.

Important Notice: Holcim recruiters only contact candidates via official @holcim.com email addresses. We do not use Gmail or other non-Holcim domains for recruitment processes. Please verify the sender address before responding.