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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientist - **Company:** Synergetic - **Location:** London, UK - **Experience:** Expert - **Contract:** Temporary contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Engineering, Continuous Integration, Extract Transform Load (ETL), Data Mining, Query Languages, Distributed Systems, Graph Database, Python (Programming Language), Machine Learning, Neo4j, Software Architecture, Software Deployment, Software Engineering, Systems Integration, Unstructured Data, Google Cloud, Retrieval-Augmented Generation, Large Language Models, Deep Learning, Generative AI, Kubernetes, Machine Learning Operations, Data Pipelines, Docker, Legacy Systems, Microservices - **Published:** October 14, 2026 - **Apply:** https://www.careerboard.com/gb/en/find-jobs-in-United-Kingdom/-F1F7CA5C55BD4E4934/ ## About the Role * 5+ years of experience in Data Science, Machine Learning, AI Engineering or related software engineering roles. * Hands-on experience designing, building and deploying AI/ML solutions into production. * Practical experience developing and implementing Knowledge Graphs. * Experience working with graph databases such as Neo4j and query languages such as Cypher. * Experience with Large Language Models (LLMs), RAG architectures and AI-powered data extraction. * Strong Python programming skills, including relevant machine learning and data science libraries. * Experience with causal machine learning, causal inference and probabilistic modelling. * Experience developing Back End integrations, APIs, ETL processes and data pipelines. * Working knowledge of Microsoft Azure and cloud-based AI infrastructure. * Understanding of microservices, distributed systems and software architecture. * Experience with MLOps, CI/CD and production deployment practices. * Experience validating AI outputs, implementing testing processes and maintaining data quality. * Ability to communicate technical concepts clearly to non-technical stakeholders. * Comfortable contributing to solution architecture while remaining actively involved in development and coding. Desirable Skills & Experience * Experience delivering Knowledge Graph-grounded or hybrid RAG solutions in production. * Experience working in regulated environments, particularly Healthcare, Life Sciences or Financial Services. * Knowledge of quality management, validation, design controls and traceability standards such as ISO 13485 or IVDR. * Experience modernising Legacy systems or converting unstructured business information into structured datasets. * Previous consultancy experience, particularly delivering projects within fast-paced client environments. * Experience with additional cloud platforms such as AWS or Google Cloud. * Familiarity with Kubernetes, Docker and container orchestration. * Experience with deep learning frameworks and NLP. * Previous experience as a Technical Lead, AI Architect or Principal Data Scientist. * Industry experience across Healthcare, Life Sciences, Financial Services, Industrials, Telecommunications or Infrastructure. Ideal Candidate We are particularly interested in candidates who combine strong technical knowledge with practical delivery experience. You may currently be working as a Senior or Principal Data Scientist, AI Engineer, Machine Learning Engineer or AI Solutions Architect. You should be comfortable designing AI architectures while remaining hands-on with Python, Knowledge Graphs, LLMs and production engineering. Experience delivering AI solutions in complex or regulated environments, working with business stakeholders and taking ownership of technical delivery would be particularly valuable. Location London, UK ## Description We are looking for an experienced Full Stack Data Scientist to design, develop and deliver production-ready AI solutions. This role combines data science, AI engineering and hands-on solution architecture, with a particular focus on Knowledge Graphs, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) and machine learning. The successful candidate will have experience taking AI solutions from proof of concept through to production, integrating them with existing systems and ensuring they are scalable, reliable and fit for business use. You will work closely with engineering teams, architects and business stakeholders to develop practical AI solutions across complex environments., * Design, develop and deploy AI and machine learning solutions, taking projects from initial concept through to production. * Build and maintain Knowledge Graphs, including graph databases and graph-based data models. * Develop LLM-powered applications and Retrieval-Augmented Generation (RAG) solutions, including Knowledge Graph-based RAG. * Design and implement causal inference systems and probabilistic models. * Develop data extraction, transformation and validation processes for structured and unstructured data. * Build and integrate AI solutions with Back End systems, APIs, data pipelines and ETL processes. * Ensure AI outputs are accurate, reliable and appropriately validated. * Work within solution architecture frameworks, contributing to technical design and architectural decisions. * Collaborate with technical and non-technical stakeholders to translate business requirements into working AI solutions. * Support the deployment, monitoring and ongoing improvement of AI applications in production environments. * Apply appropriate testing, documentation, traceability and quality assurance practices throughout development.