Full-Stack Data Scientist

Job Description:

ArcelorMittal est le numéro un mondial de l'exploitation sidérurgique et minière, avec une présence dans 60 pays et une empreinte industrielle dans 17 pays. Engagés dans la production d'un acier sà»r et durable, nous sommes le principal fournisseur d'acier de qualité des grands marchés sidérurgiques mondiaux, incluant l'automobile, la construction, l'électroménager et l'emballage. Nous sommes le plus grand producteur d'acier en Amérique du Nord, en Amérique du Sud et en Afrique, un producteur majeur au sein de la CEI et nous avons une présence croissante en Asie, notamment en Chine et en Inde. Nous sommes aussi le plus grand producteur d'acier dans l'Union Européenne avec une présence significative en France, Allemagne, Belgique, Espagne, Luxembourg, Pologne, République Tchèque et Roumanie. ArcelorMittal a son siège social au Luxembourg. Au niveau national le groupe dispose de 8 sites à travers le pays, comprenant les centres corporate à Luxembourg-Ville et à Esch-sur-Alzette, différentes unités de production d'acier pour les produits longs et tréfilés, ainsi que des centres de distribution et de maintenance. ArcelorMittal dispose également d'un centre de R&D situé à Esch-sur-Alzette.
ArcelorMittal Europe Long Products (AME LP) is operating a network of 10 steel plants, 17 rolling mills and multiple downstream units, producing and commercializing over 9 million tons per year. Aiming to optimize its operations, AME LP is looking for a Full-Stack Data Scientist to join the central marketing department to take a key role in the pricing team and the digitalization transformation. Pricing is the motor driving any industry. Our team specializes in delivering analytics/AI/ML based pricing solutions to various businesses within the ArcelorMittal Long Products organization. As a part of this role you will get a chance to work with the latest technologies in the domain of ML and data science in general. The main responsibilities will include designing, delivering, and maintaining end-to-end production ready AI and pricing solutions. This involves interaction with marketing and sales teams to continuously improve pricing solutions through better business domain knowledge. Your role: As V.I.E Full-Stack Data Scientist, you will play a vital role in helping to turn ideas into data solutions that improve pricing strategies and processes in our commercial function. You will interact with IT, finance, R&D and sales teams to support the performance of the business divisions and drive multi-system developments from design to deployment. You also will energetically support the change management. Key Responsibilities: Your will play a key role in commercial strategic and data-driven solutions and will be responsible to : Design, implement, and maintain robust IT infrastructure to support data science workflows, including Kubernetes-based deployment environments and CI/CD pipelines. Maintain and enhance internal React-based web application used by the data science team. Collaborate with data scientists to ensure seamless deployment of models as APIs into production environments using MLOps best practices. Contribute to the design and implementation of new algorithms for pricing in various business domains. Continuously improve and refactor existing pricing models for performance, scalability, and maintainability. Build tools and processes to monitor model performance, data quality, and system reliability. Ensure adherence to programming best practices, including code quality, documentation, and security standards

Candidate Requirements:

Qualifications: Master's degree in computer science or related fields. Minimum of 2 years of experience with Kubernetes and DevOps tools such as Azure/AWS, Docker, Git, Kubernetes, Linux, Airflow, CD/CI, FastAPI, MLflow, etc. Proficiency in React.js/NextJS and frontend build/deployment pipelines for maintaining internal web application. Strong Python, JavaScript and SQL skills, especially for backend services and integrating ML models. Strong problem-solving and analytical skills, with the ability to collect, analyze, and interpret complex data sets. Excellent communication and interpersonal skills to build relationships with internal and external stakeholders. Fluency in English is required, knowledge of additional European languages is a plus. It's a plus if you also have the following: Experience with deploying machine learning models in production Experience in any of the following areas: business strategy, financial analysis, marketing, pricing is an asset Experience working in the steel industry in office and plant environments