As one of Luxembourg AI Factory (AIF) consortium members, the Luxembourg National Data Service is building its capacity towards establishing the full suite of envisioned AI Factory services. Within the scope of this project, a Data Scientist will contribute to data quality assurance, data pipeline development, and model training infrastructure. to the metadata catalogue content and data quality improvement as part of the service capacity. 

As a Data Scientist on the project, you will be responsible for following the evolvement of European metadata standards extracting and populating metadata for the Luxembourg AIF catalogue. This includes the collection and validation of metadata from different data providers, standardising the information into a defined metadata model, importing and validating the metadata in the catalogue, improving data quality, and supporting the implementation of the cataloguing tools. You will work with the other project team members from LNDS and other consortium members, including Project Coordinator, Work Package Leaders, Data Protection Officer (DPO) and ethical, legal and societal implications (ELSI) experts. Finally, you will interact with the information security, technology, and data teams to ensure adequate design and delivery of services.

• Proactively collaborate with and guide the data providers to standardise metadata.  
• Develop pipelines to improve the quality of metadata and data for the project.  
• Contribute to the AIF Data Catalogue by populating, curating, and updating metadata for datasets. 
• Provide training on metadata model, tools, and data quality improvements related to the (meta-) data content services of the project.  
• Engage in (inter-)national projects related to development and improvement of (meta-)data in AI use.  
• Provide support to other projects of the Data Science Team where necessary.  

• Master's degree in science or technology.  
• 2 to 5 years of relevant experience in data analysis, data curation, data standardisation or data quality assurance in collaborative projects or services.  
• Experience in the whole life cycle of data analysis (e.g. identifying analysis goals and requirements, developing concepts, developing analysis plan, identifying methodologies, performing analysis, communicating outcomes as report/publication/presentation).  
• Working knowledge of data models, data standards, and ontologies.  
• Knowledge of data curation, ETL, and QA processes.  
• Knowledge of command line shell (any OS).  
• Knowledge of one (scientific) programming language (preferably Python or R).  
• Knowledge of FAIR principles and their application in different domains (data, software, training etc).  
• Excellent scientific and technical writing skills (documentation, report, etc).  
• Excellent verbal communication skills in English. Any other Luxembourgish National language (Luxembourgish, French, German) is a plus.  

Nice to have  

• Knowledge of European legal frameworks including GDPR, DGA, EHDS and AI Act.  
• Experience in metadata registries and/or building data catalogues.  
• Experience in advanced statistics and data analysis methods (e.g. machine learning).  
• Working knowledge of minimum data standards of various data types in the above-mentioned domains.  
• Working knowledge of code management tools (github, gitlab).