Data Scientist 6 months’ initial contract £500- £600 pd outside IR35 3 days Central London
Job Overview Stanton House has partnered with a media business based in Central London, that is looking to hire an Interim Data Scientist / AI Engineer.
Our client is building out a new data science and AI function focused on developing AI agent capabilities and embedding AI into business processes. This role will play a key part in shaping and delivering production-grade AI systems. This is a hands-on contract role suited to someone who can operate independently, take ownership, and deliver high-impact AI solutions in a fast-evolving environment.
Responsibilities
Design and build LLM-powered AI agents and multi-agent systems for real-world business applications
Develop agentic workflows, incorporating RAG, reasoning, planning, and tool orchestration
Build and deploy production-grade GenAI systems, not just prototypes
Integrate AI solutions into existing business systems, APIs, and workflows
Contribute to or establish MLOps frameworks (e.g. Databricks or similar environments)
Work closely with stakeholders to translate business problems into technical AI solutions
Own delivery end-to-end, operating with minimal supervision
Communicate complex technical concepts clearly to non-technical stakeholders
Skills Needed
Strong experience delivering machine learning and AI systems
Strong expertise in LLMs, Generative AI, and RAG systems
Proven experience building AI agents / agentic systems
Hands-on experience with LangGraph and/or similar frameworks
Strong Python engineering skills with experience building scalable systems
Experience with MLOps and ML platforming (e.g. Databricks or equivalent)
Experience designing and deploying systems on cloud platforms (AWS preferred)
Strong understanding of system design, orchestration, and production constraints
Ability to work independently, take ownership, and proactively drive work forward
Strong communication skills, with the ability to engage stakeholders and translate technical detail into business context