Team: You will join the AI Business Unit, a community of about 200 AI & Data consultants who help organizations work end to end: AI strategy and roadmaps; identification and prioritization of AI use cases; Data & AI governance; operating models for Data & AI; AI governance and Responsible AI; adoption and change management.

Your role: As a Senior Consultant in Data Science, you will play a key role in the design, industrialization, and orchestration of advanced AI solutions. Your work will go beyond PoCs; you will be at the core of industrializing AI within organizations. Here are some areas where we are looking for experts:

- Design and evolve client Data & AI foundations: define and implement modern data architectures (data lake / lakehouse, data warehouse, data mesh, data products) supporting analytics, ML, and GenAI; build robust data pipelines (batch, micro-batch, streaming) from ingestion to exposure (BI, APIs, ML features, RAG). - Industrialize AI & GenAI & BI use cases: work alongside Data Scientists / AI Engineers to move from PoC to production: model packaging, workflow automation, implement MLOps / LLMOps best practices. - Design and operate GenAI components: pipelines for RAG, vector DB, observability tools for LLMs, prompt management, secure calls to models. - Contribute to data & AI platform deplo

Team: You will join the AI Business Unit, a community of about 200 AI & Data consultants who help organizations work end to end: AI strategy and roadmaps; identification and prioritization of AI use cases; Data & AI governance; operating models for Data & AI; AI governance and Responsible AI; adoption and change management.

Your role: As a Senior Consultant in Data Science, you will play a key role in the design, industrialization, and orchestration of advanced AI solutions. Your work will go beyond PoCs; you will be at the core of industrializing AI within organizations. Here are some areas where we are looking for experts:

- Design and evolve client Data & AI foundations: define and implement modern data architectures (data lake / lakehouse, data warehouse, data mesh, data products) supporting analytics, ML, and GenAI; build robust data pipelines (batch, micro-batch, streaming) from ingestion to exposure (BI, APIs, ML features, RAG). - Industrialize AI & GenAI & BI use cases: work alongside Data Scientists / AI Engineers to move from PoC to production: model packaging, workflow automation, implement MLOps / LLMOps best practices. - Design and operate GenAI components: pipelines for RAG, vector DB, observability tools for LLMs, prompt management, secure calls to models. - Contribute to data & AI platform deplo