Data Scientist

Responsibilities :

Responsibilities

Develop AI applications using state-of-the-art (Gen)AI technology.

Translate business requests into AI applications.

Pilot prototypes in production processes to demonstrate their value.

Deploy prototypes to production to obtain reliable, scalable systems.

Present your results in a clear manner and discuss them with multi-functional project teams.

Work in close collaboration with business experts (e.g. for requirement gathering, data source identification, data and process understanding, feature engineering, result validation, etc.), and with other AI engineers in the team (e.g. for knowledge sharing).

Technical and Professional Requirements:

Technical skills

Strong expertise in Python

Strong knowledge of state-of-the-art AI and statistical methods

Proven proficiency with deploying scalable AI applications to production

Experience using LLM's and commonly used libraries to interact with LLM's (Langchain, Llamaindex, ...)

Hands-on experience with Azure Cloud, and Azure Data & AI services

Strong Expertise with version control (Git, GitHub)

Expertise with CI/CD pipelines, and modern software development best practices

Experience with Agentic AI frameworks (Langgraph, AutoGen, CrewAI, …) is a big plus

Experience with MLOps tools and frameworks (e.g. MLflow, Kubeflow, TFX) is a big plus