Senior Reliability Data Scientist

Holcim 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®.

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As 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.

We are looking for an innovative senior reliability data scientist, motivated to solve the bigger challenges in our industry. Inspired to develop and deploy applications that enhance a new era of maintenance, our Senior Reliability Data Scientist is passionate about leveraging digital tools to improve work for our 10,000 people operating our Plants of Tomorrow. You will ensure that M‑Predict is natively integrated with other Plant of Tomorrow technologies, helping our maintenance team to realize our vision for the Plants of Tomorrow.

• Machine Learning model design, tuning, configuration and validation
• Configure models to identify Mechanical/ electrical failures from historical logs and reports by coordinating with researchers and domain experts (the log creators).
• Develop and deploy a classifier model to predict equipment failures based on features from historical failure logs.
• Use a deep learning autoencoder to flag risks and anomalies for predictive maintenance in a system‑of‑systems framework.
• Create maintenance metrics to be displayed in the UI as required by the stakeholders
• Migration of existing systems to new platforms
• Responsible for the end‑to‑end lifecycle of the models (including design, deployment, tuning, and retraining)
• Collaborate closely with stakeholders to understand business requirements and desired capabilities through user stories, to ensure what we develop is valuable for our users.
• Ensure the successful delivery of solutions and manage their ongoing enhancement roadmaps
• Drive uptake and utilization of deployed technologies in the field through proper onboarding and training, gathering frequent feedback from the user community

• 3 years experience of applied machine learning on projects for machinery in heavy industry
• 2 years experience with productizing ML models in cloud and on premise
• 2 years experience in change management to guarantee the full adoption and implementation of the new technologies in heavy industry
• 2 years experience in coaching and know‑how transfer of complex projects

• Applied Machine Learning experience (Anomaly Detection, regression analysis, time series, probabilistic models, supervised classification, and unsupervised learning)
• Strong mathematical background (linear algebra, calculus, probability, and statistics)
• Experience with scalable ML (Map Reduce, streaming)
• Knowledge in electrical engineering and cyber‑physical systems
• Ability to drive a project and work both independently and in a team
• Data analysis and visualization (Jupyter, Seaborn)

MS or PhD in Computer Science, Electrical Engineering, Statistics, or equivalent fields

C3 AI Certifications (C3 AI Data Science, C3 AI V8 Data Science, C3 AI V8 Application Development, C3 AI Development Core) (advantage)

• English (technical fluency critical)
• Spanish, German and French are an advantage

• Family Support:
  Subsidized childcare and paid maternity/paternity leave
• Professional Growth:
  Company‑sponsored training and professional development.
• 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 committed to a diverse and inclusive workplace. We support equal opportunities for everyone, regardless of race, national origin, gender, sexuality, disability, or age.