Senior Data Scientist (RAG & Document Intelligence)

Quick Facts

• Role: Senior Data Scientist focused on RAG & Document Intelligence
• Work model: Fully remote
• Engagement: Full-time (B2B contract)

Description

You will build repeatable, explainable, and scalable AI-driven business insight solutions for an international Consumer Health organization. The role combines structured data and business knowledge with retrieval-augmented generation (RAG), knowledge graphs, and deterministic analytics—balancing flexible LLM behavior with reliable analytical logic. You will also evaluate and improve quality, trust, consistency, and enterprise scalability of outputs.

Responsibilities

• Translate business questions into repeatable, explainable analytical approaches grounded in trusted data
• Integrate structured data and knowledge from multiple sources, using RAG and knowledge graphs to connect metrics, entities, concepts, and business context
• Create reusable analytical “recipes” with explicitly defined data, calculations, analytical steps, decision logic, and expected outputs
• Experiment and evaluate statistical/ML techniques and LLM workflows (retrieval strategies, semantic models, knowledge graphs, prompts, agentic workflows), including building evaluation datasets and defining accuracy, relevance, consistency, robustness, latency, and cost metrics
• Verify outputs are supported by underlying data and maintain consistent, reproducible, explainable results across brands, markets, and time periods

Requirements

Must-have

• Strong Python skills with production-grade code for machine learning and generative AI workflows
• Strong experience with structured data and analytical methods (data exploration, statistical analysis, feature engineering, hypothesis testing, segmentation, trend and driver analysis)
• Experience applying generative AI and LLMs to analytical and knowledge-intensive use cases (prompt engineering, structured outputs, tool/function calling, context engineering, RAG)
• Ability to balance probabilistic AI techniques with deterministic analytical methods
• Understanding of data semantics and knowledge representation (semantic models, ontologies, and/or knowledge graphs)
• Experience with AI/analytics evaluation and quality metrics (e.g., RAGAS, DeepEval, Langfuse)
• Familiarity with multi-agent AI frameworks (LangGraph, LangChain, or Pydantic AI)
• Experience with vector databases (pgvector, Pinecone, Qdrant, Weaviate)
• Experience with Azure cloud services (Azure Apps, Containers, Storage, AI Search, AI Foundry) and/or AWS equivalents
• Experience with Databricks (Delta Lake, Unity Catalog, MLflow)
• Structured, experiment-driven analytical problem-solving mindset
• Fluent English (written and spoken)

Nice-to-have

• API and MCP development and integration (FastAPI, FastMCP)
• Experience applying analytics and AI to Consumer Health, FMCG/CPG, marketing, consumer insights, or brand performance
• Experience building production-grade, end-to-end agentic AI solutions (full-stack development)
• Experience with Aegra (open-source, self-hosted Agent Protocol server for running AI agents)

Benefits

• B2B contract with individually negotiated rate (up to 200 PLN net/h + VAT)
• Fully remote service delivery
• Broad range of internal and international projects
• Budget for skills development and certifications
• Regular collaboration reviews and discussions about project scope
• Additional benefits available via the collaboration
• Networking and team-building events for project teams