Data Scientist

🚀 Data Scientist | Graph AI, Knowledge Graphs & Modern LLM/RAG |

AI Incubator Platform 🌍 Remote | 📄 B2B Contract |

We are seeking a hands-on Data Scientist and AI Builder to turn cutting-edge research concepts into production-ready data products and intelligent systems. Working with an in-house technology consultancy at a global consulting firm, you will operate across agile innovation pods—architecting graph-centric AI, building enterprise knowledge graphs, and engineering production-grade NLP/LLM retrieval workflows across a 3–5 year horizon.

What You’ll Be Doing:

• Designing and implementing graph-centric AI architectures, graph data science workflows, and knowledge graphs (schema/ontology, entity resolution) using Neo4j and GNNs (GCN/GAT).
• Engineering end-to-end LLM capabilities, including prompt/tool design, grounding strategies, semantic parsing (text-to-SQL), fine-tuning, and robust RAG pipelines.
• Training, evaluating, and iterating on core ML/DL models with rigorous error analysis, drift detection, and offline evaluation harnesses.
• Developing production-ready batch and real-time APIs/services to expose model, retrieval, and graph capabilities with strict performance targets.
• Taking end-to-end ownership in agile pods, writing clean Python code, automated test suites, CI checks, and operational runbooks.
• Optimizing model inference and training pipelines for accelerated compute (GPUs) and distributed processing.

What We’re Looking For:

• Proven commercial track record (3–6+ years) in applied Data Science, Machine Learning, and Python software engineering.
• Strong ensemble background combining deep ML/DL fundamentals with practical depth in Graph AI and modern NLP/LLM engineering.
• Consultant mindset: proactive problem solver who thrives in fast-changing frontier environments, embraces ambiguity, and communicates complex AI logic clearly.
• Solid experience in system observability, model drift monitoring, data lineage, and reproducible ML workflows.

Must-Haves:

• 3–6+ years of production Python software engineering experience.
• Strong grounding in Core ML, Deep Learning, and experiment design.
• Hands-on experience building RAG architectures, retrieval/search systems (lexical, vector, hybrid), and agentic workflows.
• Exposure to knowledge graph modeling, graph databases (e.g., Neo4j), and graph representation learning/GNNs.
• Familiarity with cloud environments (Azure, AWS, or GCP) and CI/CD practices.
• Excellent English communication skills for daily cross-functional collaboration.

Location & Working Setup:

• 100% Remote working model (Candidates must be living and working within the EU)
• US Hours overlap needed: Minimum 2:00 PM – 6:00 PM CET (Preferred 2:00 PM – 7:00 PM CET).
• Availability for quarterly 1–3 day team workshops/gatherings in Prague (all travel and accommodation expensed).

Ready to build the intelligence and architectures that define next-generation AI platforms? Apply today or send your CV directly to get started!