Senior Data Scientist
Posted Updated
Description
Context:
A team responsible for the development and industrialization of applications for the Investment Banking division. Accelerating the integration of generative AI solutions and AI agents into business processes. A strategic environment within the platform, with high-impact use cases in document analysis, credit, and finance.
- Strong Python with extensive experience in Object-Oriented Programming and enterprise software design patterns.
- Proven track record building asynchronous microservices and endpoints using FastAPI.
- Hands-on practice in pytest (unit, functional, and integration testing for ML/LLM pipelines).
- Bash scripts for automation, data handling, and container interaction.
- LLMs architecture understanding proven by project portfolio.
- Architecting multi-step, stateful agentic graphs using LangGraph or Google ADK.
- Hands-on experience optimizing LLM pipelines programmatically using DSPy.
- Practical knowledge of deploying and running high-throughput open-weight models on GPU infrastructure using runtimes such as vLLM (experience with CUDA and fine-tuning is a strong plus).
- Hands-on familiarity with automated build, test, and release pipelines (Jenkins).
- Experience setting up tracing, drift detection, and automated evaluations for generative workflows using tools like Phoenix Arize.
- Dedication to shipping stable, secure code into flagship banking infrastructure where compliance, auditability, and data security are non-negotiable.
- General Stack: Google ADK, LangGraph, DSPy, vLLM, FastAPI, Python, Pytest. Arize Phoenix. Kubernetes, Jenkins, GPUs.
- Nice to have - Corporate Institional Banking project experience.