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• Analyze and optimize key logistics processes using data-driven insights.
• Collaborate closely with our warehouse team to identify improvement opportunities.
• Develop practical data driven tool that will be implemented in daily operations to enhance efficiency and strengthen communication with other critical Hilti stakeholders.
• Learn by doing: gain exposure to real-world challenges in supply chain and logistics while applying your analytical skills to create solutions that matter.

Clearstream, part of the Deutsche Börse Group, is a leading global provider of post-trade services, offering settlement, custody, and collateral management solutions. Our expertise ensures stability, efficiency, and transparency in financial markets worldwide.

The Model Validation Team plays a critical role in ensuring the robustness, accuracy, and compliance of the risk models used at Clearstream. This is your chance to gain hands-on experience in a high-stakes environment, working with professionals who validate cutting-edge financial models.

Your responsibilities:

• Assist in validating risk models used for operational risk, credit risk, market risk, and liquidity risk management.
• Help perform statistical analyses and backtesting to assess model performance.
• Assist reviewing model assumptions, methodologies, and limitations.
• Help develop and run stress-testing frameworks to evaluate model robustness under extreme scenarios.
• Research innovative approaches to enhance model accuracy and validation processes.
• Support the team with document findings and prepare validation reports in alignment with regulatory requirements (e.g., CSDR, MaRisk).

Participation au projet « Dynamique QRM » (Quality Risk Management) sur le site de Chartres :

• Contribuer à la visibilité du projet : mise à jour et amélioration de la page intranet dédiée à la communication ;
• Participer aux actions opérationnelles permettant de faire avancer le projet ;
• Développer un outil de visualisation des risques ;
• Collaborer avec des équipes de différents départements (production aseptique, production produits finis, etc) et échanger avec des interlocuteurs basés sur d’autres sites internationaux.

Immersion dans la routine d’un AQ opérationnelle en production aseptique :

• Participation aux activités terrain en zone aseptique aux côtés des équipes de production ;
• Revue des dossiers de lots ;
• Revues des logbooks équipement ;
• Identification des activités AQ pouvant être optimisées grâce à l’utilisation de l’IA.

The aim of this internship project announcement is to establish a reserve list of successful candidates for various teams in the Capabilities Directorate of Europol. Based on the profile of the successful candidates, the intern will be allocated to one of the units/teams listed below:

ICT Strategy & Execution Coordination Unit

This internship project focuses on supporting the management of multiple sourcing initiatives and engagement with suppliers within the ICT Unit which will run in parallel.

The following two internship projects are available in this team:

• A. The internship project will be focussed on providing project support for the launch of Europol's new real time communication solution based on Stashcat technology.
• B. The internship project will focus on providing project support for the launch of two new projects, the - Digital Single Place (DSP) and the EU Information Management Wider Landscape together with the usual European Platform for Experts (EPE), which will actually interact with the DSP.

• Collaborating with multidisciplinary, international teams
• Ensuring compliance with safety and regulatory standards (e.g., DO-178C, ISO 26262)
• Participate in the verification and validation (V&V) process of AI models, ensuring compliance with system and safety requirements
• Contribute to the design and execution of test cases for AI components
• Support the collection, curation, and labeling of datasets for model training and evaluation
• Assist in the training, fine-tuning, and performance monitoring of AI/ML models using Python and AI frameworks (e.g., TensorFlow, PyTorch, scikit-learn)
• Develop and maintain automated pipelines for model training, testing, and deployment
• Analyze model behavior and performance, and contribute to debugging and improving AI models
• Contribute to the continuous improvement of AI development and verification processes through automation and DevOps practices
• Stay up to date with the latest AI/ML technologies and contribute ideas for integrating innovative solutions into existing workflows.