AI Data Scientist

Brussel, Brussel

AI Data Scientist with Business Mindset and Expertise in Generative AI

Expected Start Date: As soon as possible
Duration: 24 months (with potential for extension depending on project evolution)

Collaborate with business and technical teams to identify high-impact use cases for Generative AI.
Design, develop, and implement AI-driven solutions for business needs using both internal and external data sources.
Identify and communicate insights from data analysis to support decision-making and problem-solving activities.
Collaborate with cross-functional teams to identify and resolve data-related issues.
Continuously monitor AI models for accuracy and proactively identify and resolve data discrepancies and drift.
Contribute to the development of a GenAI capability framework and internal best practices.

Education: Master's degree in a quantitative field (e.g., Statistics, Mathematics, Computer Science, Economics, Business) or a related field with a strong focus on data analysis.
Experience: 5 to 8 years in data science, preferably in a business setting.
Strong business acumen and the ability to understand and communicate business needs and requirements.

Proven experience with data wrangling, statistical analysis, predictive modeling, and machine learning.
Proficient in Python and commonly used libraries (Pandas, NumPy, Scikit-learn, etc.).
Strong knowledge of cloud platforms, especially Azure (Azure AI services, Azure ML, Vertex AI, Databricks, Azure OpenAI, etc.).
Deep expertise with Python libraries such as Langchain, LangGraph, Promptflow, Semantic Kernel, and Autogen.
Deep understanding of LLMs fine-tuning and/or training lifecycle (LLMops).
Proven experience in deploying and monitoring GenAI models using CI/CD pipelines, Weight & Biases, and GitHub workflows.
Strong knowledge of data analysis techniques and tools, such as Python, SQL, PBI, and DataBricks.