Job Overview
Join to apply for the Researcher in Predictive Modelling role at ArcelorMittal Long Carbon LATAM.
ArcelorMittal is the world’s largest steel and mining company. We use innovative technologies to create the steels of tomorrow’s world. Every day over 125,000 of our talented people, located in over 60 countries, push the boundaries of digitalization, and use advanced technologies to create a stronger, faster, and smarter world.
Comprising 1,650 researchers across 14 Research Centers, our Global R&D team continuously improves steel quality and manufacturing processes. The Digitalisation team within the R&D Spain Lab provides worldwide service to the group, delivering AI and data science solutions for manufacturing, product development, environmental, decarbonisation, supply chain, commercial, planning & scheduling, and more.
Responsibilities
We’re looking for a curious and driven individual with a strong technical background to join our team and help shape the future of industrial intelligence. You’ll bring expertise in data science, machine learning, and signal processing, and apply it to real-world challenges in manufacturing and industrial environments. Whether it’s working with sensor data, uncovering patterns in time‑series signals, or developing smart diagnostics for industrial machinery, you’ll be at the forefront of innovation. You should be comfortable navigating complex datasets, building scalable solutions, and collaborating across disciplines in fast‑paced R&D settings.
Qualifications
* Master’s or PhD in Data Science, Computer Science, Industrial Engineering, Applied Mathematics, or related field
* Strong foundation in machine learning, deep learning, and statistical modeling, including experience with Bayesian methods and probabilistic algorithms
* Proficiency in Python and relevant libraries for data analysis, machine learning, and signal processing
* Experience with time‑series analysis, anomaly detection, and condition monitoring
* Solid understanding of signal processing techniques and their application to industrial data
* Experience with sensor data acquisition systems and industrial instrumentation
* Familiarity with diagnostics technologies such as vibration analysis, current analysis, acoustic monitoring, and other condition monitoring methods
* Knowledge of various industrial assets (e.g., motors, pumps, fans), their typical failure modes, and how these manifest in different monitoring technologies
* Experience working with large‑scale datasets from industrial systems and IoT environments
* Knowledge of cloud‑based data architectures and scalable data processing
* Comfortable working in multidisciplinary teams and collaborative R&D environments
* Strong interest in industrial manufacturing processes and Industry 4.0 applications
* Well‑organized and capable of contributing to multiple research initiatives in parallel
* Proficiency in English is mandatory; a good level or willingness to learn Spanish is desired
Seniority Level
* Entry level
Employment Type
* Full-time
Job Function
* Finance and Sales
Industries
* Mining
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