Researcher in Predictive Modelling

ArcelorMittal Aceros Largos LATAM; Avilés; Presencial; EUR 40.000 - 60.000; Jornada completa

Descripción de la vacante

A leading global steel manufacturer in Avilés is seeking a Data Scientist to work on industrial intelligence challenges. This role involves applying data science and machine learning to enhance manufacturing processes through advanced diagnostics and analysis of sensor data. Ideal candidates will have a Master's or PhD in a relevant field, strong technical skills, and a passion for Industry 4.0 technologies. Join us to impact major industries and contribute to sustainable energy solutions.

Formación

• Master’s or PhD in Data Science, Computer Science, Industrial Engineering, or related field.
• Strong foundation in machine learning, deep learning, and statistical modeling.
• Proficiency in Python for data analysis and machine learning.
• Experience with time-series analysis and condition monitoring.

Responsabilidades

• Apply data science and machine learning to real-world manufacturing challenges.
• Analyze sensor data to uncover patterns in time-series signals.
• Develop diagnostics for industrial machinery.

Conocimientos

Machine learning

Data analysis

Python

Signal processing

Time-series analysis

Anomaly detection

Educación

Master's or PhD in Data Science or related field

Herramientas

Relevant libraries for data analysis

Descripción del empleo

Job Description

ArcelorMittal is the world’s largest steel and mining. We use the most innovative technologies to create the steels tomorrow’s world will be made of. 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. To help make this possible, they know they can depend on the support and training that a company of our scope and scale can provide.

Comprising 1,650 researchers spread across 14 Research Centers around the world, our Global R&D team aims to continuously improve the quality of steel and its manufacturing processes. This involves investigating and developing disruptive technologies, reducing the carbon footprint of steel, and optimizing costs while maintaining uncompromising quality.

The team's strong multicultural diversity, with over 30 nationalities, offers international experience and makes it possible to meet global needs.

The Digitalization team is part of the ArcelorMittal R&D Spain Lab and it provides worldwide service within the ArcelorMittal Group. We are a team of more than 70 researchers working on Digitalization and Artificial Intelligence applied to a wide range of activities (manufacturing, product development, environmental, decarbonization, supply chain, commercial, planning & scheduling, etc.). This multidisciplinary team covers a wide variety of scientific and business areas with highly qualified researchers (engineers, mathematicians, physicists, etc.), all of them with deep expertise in combining Science and Business know‑how. Their enthusiasm and commitment create an incredible working atmosphere for those that want to enjoy the experience of researching and applying breakthrough ideas in the real industrial world.

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. A passion for industrial technologies, condition monitoring, and the evolving landscape of Industry 4.0 will help you thrive in this role. If you enjoy solving tough problems, working with cutting‑edge tools, and contributing to multiple research initiatives, we’d love to hear from you.

Qualifications

• Master’s or PhD in Data Science, Computer Science, Industrial Engineering, Applied Mathematics, or a 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 and a good level or willingness to learn Spanish is desired

Join us and you’ll see your work help create renewable energy, impact major industries and boost economies. At ArcelorMittal we’ll help you make your worl