- Data Scientist

Context / objectives of the role We are seeking a talented AI Data Scientist with a strong business mindset and deep expertise in Generative AI. The successful candidate will operate in a dynamic environment and leverage their analytical skills to solve complex business challenges. Mission period Start Date: As soon as possible Duration: 24 months (extension possible depending on project evolution) Location: Based in central Brussels Key responsibilities Collaborate with business and technical teams to identify high-impact use cases for Generative AI. Design, develop, and implement AI-driven solutions using both internal and external data sources. Extract and communicate insights from data to support decision-making. Work with cross-functional teams to address data-related issues. Monitor AI models for performance, ensuring accuracy and addressing discrepancies or data drift. Contribute to the development of a Generative AI capability framework and internal best practices. Profile Language requirements English: Good proficiency (spoken, written, reading) Dutch: Good proficiency (spoken, written, reading) French: Good proficiency (spoken, written, reading) Education requirements: Master's degree in a quantitative field (e.g., Statistics, Mathematics, Computer Science, Economics, Business) or related area with strong emphasis on data analysis Required knowledge and experience Personal skills (mandatory) Ability to work independently and in a team Manage multiple priorities effectively Meet tight deadlines Willingness to travel occasionally and work on projects in other operating companies Business experience (mandatory) 5-8 years of experience in data science, ideally in a business context Strong business acumen with the ability to understand and articulate business needs and translate them into technical solutions Technical skills (mandatory) Expertise in data wrangling, statistical analysis, predictive modeling, and Machine Learning Proficiency in Python and common libraries (e.g., Pandas, NumPy, Scikit-learn) Cloud expertise, especially with Azure (e.g., Azure AI Services, Azure ML, Databricks, Azure Openai) In-depth knowledge of LLM libraries (e.g., Langchain, Langgraph, Promptflow, Semantic Kernel, Autogen) Experience with LLM fine-tuning and training lifecycle (Llmops) Experience deploying and monitoring Generative AI models using CI/CD pipelines, Weights & Biases, and GitHub workflows Functional skills (mandatory): Strong command of data analysis tools and platforms including Python, SQL, Power BI, and Databricks