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
