ArcelorMittal is the world's largest steel producer.
We use the most innovative technology to create the steels tomorrow's world will be made of.
Every day over 190,000 of our talented people, located in over 60 countries, push the boundaries of digitalization and use advanced technology to create a world that is stronger, faster and smarter.
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.
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 50 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.
We are looking for a researcher with knowledge of Artificial Intelligence applied to predictive maintenance.
Currently, the main research lines go through developing intelligent solutions based on analysis of vibrations, currents, voltages or temperatures.
Thus, the development of algorithms using Machine Learning techniques is mandatory.
Also, basic knowledge of electrical machines, motors, pumps, drives, etc.
and/or demonstrable experience in maintenance works in industrial facilities would be desirable.
Finally, knowledge and experience in signal processing (sensors, data acquisition systems, signal conditioning and signal processing) is also highly desirable.
Your role: Develop models for anomaly detection, time series forecasting, remaining useful life estimation and/or signal processing problems.
Support the deployment of those models in production.
Manage projects related to the application of Predictive Maintenance in our industrial facilities.
Analyze deeply each case to identify the best technical approach to be applied (signals, sensors, modeling approach, etc.).
Ensure proper and fluid communication with the maintenance teams in our plants.
Promote new innovative practices to enhance the operations of our Predictive Maintenance lab.
Stay up-to-date with emerging trends and technologies in Predictive Maintenance.
Your profile Requirements: Master's degree in a quantitative field: Mathematics, Physics, Engineering, Computer Science, Operations Research or other related field.
2+ years experience as a data scientist.
Experience with Condition Monitoring/Predictive Maintenance projects would be desirable.
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