Senior Data Scientist

Quick Facts

• Role: Senior Data Scientist (LLM/agentic systems)

Description

Join a team responsible for developing and industrializing applications for Investment Banking, accelerating the integration of generative AI solutions and AI agents into business processes. You will design LLM-based agentic solutions, build data extraction pipelines, and create evaluation and observability frameworks, then deploy high-throughput models on GPU infrastructure using testing and DevOps best practices.

Responsibilities

• Design and develop LLM-based agentic solutions to automate complex business processes.
• Partner with business teams to identify needs and drive adoption of AI solutions.
• Develop data extraction pipelines and implement evaluation and observability frameworks for AI agents.
• Deploy and industrialize models (LLMs, GPUs), ensuring quality through testing and DevOps practices.
• Own the delivery of AI features end-to-end.
• Account for LLM non-determinism by setting clear constraints and building robust safety rails.
• Test ideas and PoCs quickly, validating feasibility with data and avoiding technical debt.
• Communicate technical trade-offs clearly with architects and business users; mentor peers.

Requirements

• Strong Python with object-oriented programming and enterprise software design patterns.
• Track record building asynchronous microservices/endpoints with FastAPI.
• Hands-on pytest experience for unit, functional, and integration testing of ML/LLM pipelines.
• Ability to write Bash scripts for automation, data handling, and container interaction.
• Demonstrated understanding of LLM architecture via a project portfolio.
• Experience architecting multi-step, stateful agentic graphs using LangGraph or Google ADK.
• Hands-on optimization of LLM pipelines using DSPy.
• Experience deploying and running high-throughput open-weight models on GPU infrastructure using runtimes like vLLM (CUDA and fine-tuning are a plus).
• Experience with automated build/test/release pipelines using Jenkins.
• Experience setting up tracing, drift detection, and automated evaluations for generative workflows (e.g., Phoenix Arize).
• Strong commitment to stable, secure, compliant code for banking infrastructure (compliance, auditability, data security).

Benefits

• Work in an international consulting setting on Investment Banking applications.
• Permanent contract or B2B cooperation.
• Co-financing of training, certification exams, and postgraduate studies.
• Influence over the direction of initiatives; openness to implementing your ideas.
• Excellent working atmosphere and integration events.