Data Scientist / Data Engineer - Hybrid

Join our dynamic international team and embrace the adventure of working abroad!

For an European institution in Brussels, Belgium, we are looking for a hybrid Data Scientist / Data Engineer.

Candidates need to be based in Europe within 2 hours of Brussels.

Candidates need to be fluent in English. A work permit is required, but not provided. This position is open for contractors. .

Tasks and Responsibilities:

• Advise and assist in technology watch, evaluation studies, architectural considerations, applicable standards, solution patterns and best practices in following areas of expertise: Business Intelligence, Data Analytics, Artificial Intelligence;
• Design, development and deployment of AI-powered applications using Retrieval-Augmented Generation (RAG) and LLM-based architectures;
• Development of NLP pipelines for document processing, summarization, semantic search and conversational AI;
• Implementation of machine learning models (supervised / unsupervised) for recommendation systems, classification and prediction;
• Design and optimisation of data ingestion and transformation pipelines in cloud environments (Azure, Databricks, APIs);
• Data modelling, data analysis and preparation of datasets for machine learning and AI solutions;
• Integration of AI solutions with existing enterprise systems and data platforms.
• Contribution to the design of data lake architectures and ETL processes (Bronze/Silver/Gold layers);
• Development of analytics and reporting solutions (e.g. Power BI dashboards).
• Participation in technical working groups, progress meetings and meetings with the users;
• Assistance during relevant parts of testing, analysis, technical documentation, deployment, evaluation and reporting;

Profile:

• Bachelor's degree & 17 years of experience in IT OR Master's degree & 13 years of experience;
• +5 years of experience with data systems, information systems, or enterprise data environments;
• +3 years of experience in in Business Intelligence (BI), analytics, or enterprise reporting;
• +2 years of experience with prompt engineering and optimization for Large Language Models (LLMs);
• Strong knowledge of enterprise architecture best practices and solution design patterns;
• Solid expertise in data modelling, data warehouse, and data lake architecture.
• Experience with data mining, data preparation for Machine Learning (ML) / Deep Learning (DL) algorithms;
• Practical experience applying Machine Learning and Deep Learning methodologies in real-world solution development, deployment, or optimization;
• Strong knowledge of Natural Language Processing (NLP) technologies and applications, including semantic search, conversational AI, and text analytics;
• Proficiency with modern data science, AI, and analytics tools, including Python, Jupyter Notebook, TensorFlow, PyTorch, Haystack, and etc;
• Hands-on experience in data engineering and large-scale data processing pipelines, including ETL, APIs, Azure Databricks, and Spark;
• Strong experience with Business Intelligence and reporting platforms, particularly PowerBI;
• Experience with Docker containerization, virtualization, and deployment technologies is considered an asset;
• Familiarity with project management and Agile/Scrum delivery methodologies is an asset;
• Fluent in English;