Process Data Scientist

ppSearch by Location (Type in the city or state) /p pSelect how often (in days) to receive an alert: /p pHolcim is the leading partner for sustainable construction, creating value across the built environment from infrastructure and industry to buildings. Headquartered in Zug, Switzerland, Holcim has more than 48,000 employees in 45 attractive markets – across Europe, Latin America, Asia, Middle East Africa. Holcim offers high-value end-to-end Building Materials and Building Solutions, from foundations and flooring to roofing and walling – powered by premium brands including ECOPlanet, ECOPact, and ECOCycle®. Find out more at /p pHolcim is the leading partner for sustainable construction with net sales of CHF 15.7 billion in 2025, creating value across the built environment from infrastructure and industry to buildings. Headquartered in Zug, Switzerland, Holcim has more than 50 000 employees in 45 countries – across Europe, Latin America and Asia, Middle East Africa – and has 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 foundation and flooring to walling and roofing – powered by premium brands including ECOPact, ECOPlanet, ECOCycle, and Ytong. /p pbRole Overview /b /p pAs we continue to look for more sustainable ways to build, we need world-class talent to join our team. People who are passionate about sustainability, driven by curiosity, and keen to grow, learn, develop, and thrive in our high-performance culture. /p pWe are looking for an innovative bProcess /bbData Scientist /b, motivated to solve the bigger operational and energy challenges in our industry. Inspired to develop and deploy cutting-edge AI applications that enhance a new era of kiln and thermal efficiency, our Process Data Scientist is passionate about leveraging digital tools to optimize process stability, reduce fuel consumption, drive Alternative Fuel substitution, and curb CO2 emissions across our Plants of Tomorrow. /p pYou will work on the algorithm design, Machine Learning development and deployment, and implementation of various manufacturing process optimisation initiatives including our flagship solution bP-PREDICT /b. /p pYou will also make sure these solutions integrate seamlessly our legacy and new Plant of Tomorrow technologies to realize our vision for sustainable cement manufacturing. /p pbMain Responsibilities /b /p pbMachine Learning Physics-AI Hybrid Model Design, Tuning, and Validation: /b /p pDesign, configure, and validate hybrid Machine Learning algorithms combining 1st-principles process physics and adaptive AI loops for calciner and kiln optimization. /p pDevelop predictive soft sensors for real-time process variables, like fuel calorific value forecasting of alternative fuels and clinker quality predicting. /p pBuild multi-variable target recommenders for control loops of our kilns and other equipment /p pUse deep learning, time-series forecasting, and probabilistic models to predict operational hazards (such as ring formation risk, cyclone blockages, and pressure spikes). /p pbModel Lifecycle Management: /b /p pResponsible for the end-to-end lifecycle of models (including feature engineering, design, cloud/edge deployment, continuous tuning, and automated retraining pipelines). /p pWork with our vendors on the deployment and customization of their solutions as well as on development of Holcim proprietary solutions. /p pbExplainable AI (XAI) Operator Interface Integration: /b /p pDesign operational logic, reason codes, and metrics to be displayed on operator dashboards to ensure high explainability and user trust. /p pCollaborate closely with process engineers and plant operators to translate operational knowledge into accurate model boundaries. /p pbField Adoption Knowledge Transfer: /b /p pDrive global uptake and utilization of P-PREDICT and other PoT initiatives across the world, through structured plant onboarding, commissioning support, and feedback loops. /p pProvide coaching, knowhow transfer, and technical documentation for plant process engineers. /p pbYour Profile /b /p p bLevel of education/qualifications normally required: /b /p p bMS or PhD /bin Computer Science, Chemical Engineering, Data Science, Electrical Engineering, Systems Control, or equivalent fields. /p pC3.ai Certifications (C3.ai Data Science, C3.ai V8 Data Science/Application Development) or equivalent enterprise AI framework certification (Advantage). /p p bExperience /b /p p b3+ years’ experience /bin applied Machine Learning and Data Science projects focused on heavy industry process optimization (cement, chemical, energy, or mineral processing preferred). /p p b2+ years’ experience /bproductizing and scaling ML models in production environments (both Cloud and EDGE). /p p b2+ years’ experience /bin industrial change management, coaching, and technical knowledge transfer to guarantee full plant adoption of digital control systems (Advantage). /p p bApplied Machine Learning expertise: /bAnomaly detection, time-series forecasting, regression analysis, probabilistic modeling, supervised classification, and unsupervised learning. /p p bStrong mathematical domain background: /bLinear algebra, calculus, probability/statistics, heat and mass transfer, and basic process control dynamics (PID/MPC). /p p bProgramming ML Stack: /bHigh proficiency in Python (PyTorch, TensorFlow, Scikit-learn, Pandas, NumPy) and R/SQL; experience with prototype and production data pipelines. /p p bData Warehousing, Data Lakes Scalable Data Systems: /bPractical experience working with modern data platforms, including bBigQuery, cloud data warehouses, data lakes, and lakehouse architectures /bon platforms such as GCP or AWS. Ability to efficiently query, transform, integrate, and prepare large-scale datasets for analytics and machine learning. Experience with distributed data processing and scalable ML platforms is a strong plus. /p p bTime-Series Industrial Data Platforms: /bExperience working with time-series databases and industrial data platforms such as InfluxDB and Seeq. Familiarity with integrating sensor, process, operational, and contextual data from multiple sources is desirable. /p p bData Engineering Pipelines: /bExperience designing and working with ETL/ELT pipelines, data ingestion, data transformation, feature engineering, data quality, and production data workflows. Understanding of batch and streaming data architectures is a plus. /p p bData Visualization Explainable AI: /bHands-on experience with Jupyter, Grafana, Looker studio,Seeq, Seaborn, and other visualization tools. Experience building explainable AI solutions, including model interpretation, feature importance, anomaly explanations, and reason-code displays for technical and business users. /p p bCloud Production ML: /bExperience deploying and operating machine-learning solutions in cloud environments. Familiarity with MLOps, model deployment, monitoring, version control, CI/CD, and containerization is a plus. /p pFamily Support: Subsidized child care and paid maternity/paternity leave /p pProfessional Growth: Company-sponsored training and professional development. /p pDiscounts and Perks: Subsidized meals, exclusive discounts, and company gifts for special occasions. /p pLong-service awards /p pEmployee referral bonus /p pPension and Savings: Access to a comprehensive pension fund and an employee savings scheme. /p pHolcim is committed to a diverse and inclusive workplace. We support equal opportunities for everyone, regardless of race, national origin, gender, sexuality, disability, or age. /p /p #J-18808-Ljbffr