The business need is understood and formalized in a descriptive datasheet or specifications
The results of the analysis or the models are presented to the customers with data visualisation tools indicating the performances and the limits.
The source code is delivered and explained if necessary.

Experience deploying solutions on Azure (preferred) or other major cloud platforms
Practical experience with both proprietary (OpenAI) and open-source LLMs
Strong problem-solving skills with a focus on building, not theory
Should have practical knowledge on traditional NLP algorithms/models (BERT/Transformer based models)
Create scalable solutions on cloud platforms ( Azure preferred ) and manage the lifecycle with MLE best practices
Develop reusable agentic components
Design, build, and create LLM-powered applications and agents for automation and workflow optimization.
Prepare and process structured/unstructured datasets for fine-tuning or training models.
Leverage OpenAI APIs and open-source LLMs (e.g., GPT, LLaMA, Gemini, etc.)
The methods are identified through external researches and selected by their theoretical bases, advantages and drawbacks.

Health of the metier
The metier is well supported by the data scientist network with proposals for improvements to develop people, technos, processes.

Senior Data Scientist

Key skills