Middle Data Scientist (Modeling Automation Team)

Responsibilities: We are responsible for making development in DS faster, higher quality, and cheaper. Now we need a middle-level specialist who will take on "adhocs" and turn them into systemic solutions. You will develop MCP, integrate AI skills into the DS development environment, and improve our internal services for auto-documentation and auto-review.

• Develop MCP for automating internal AutoML tools • Integrate useful LLM skills directly into the DS team's development environment • Refine and scale AutoDoc and AutoReview services • Perform integrations into CI/CD and the bank's overall ecosystem • Quickly prototype solutions for new requests from business and DS teams (work with "adhocs" as growth drivers)

Requirements: • 1.5+ years of experience in Python development with a focus on ML/LLM solutions • Understanding of agent and MCP architecture: experience with LangChain / LangGraph, ability to design state graphs and reasoning chains for real engineering tasks • Prompt engineering for working with code (few-shot, CoT, Self-Consistency applied to Python scripts and Jupyter notebooks) • Ability to work in uncertainty: quickly grasp context, take responsibility for a whole block of functionality (from idea to deploy)

Will be a plus • Engineering background: experience in developing REST APIs, working with message brokers (queues), asynchronous programming, databases (including vector databases) • Experience in classical DS (sklearn, XGBoost, Deep Learning) • Experience developing plugins/extensions for development environments (VSCode, Jupyter) • Understanding of MLOps (MLflow, K8s, Argo/Airflow, Jenkins)

Conditions: • Work on complex products that accelerate DS work • Opportunity to influence architecture and stack • Decent, official salary, voluntary medical insurance (DMS) • Hybrid employment (3-4 days in the office, the rest remotely)