Data Scientist / Machine Learning Scientist

Location: London (Hybrid)

Duration: 6 Months

The Role

We’re hiring AI operators who ship — not experiment. If you’ve built and deployed real LLM and agentic systems in production environments, we want to talk. This is an opportunity to shape how AI is applied at scale across a global business. We’re building multiple AI teams across Informa, spanning both AI product development (SaaS / B2B) and AI-led business transformation. You will be aligned to the area where you can create the most impact — either building LLM-powered products or embedding AI into core business workflows and decision-making processes. This is a production-first environment, where the focus is on delivering systems that are used, trusted, and continuously improved.

What They’ll Work On

• You will design and build AI agents and agentic workflows powered by LLMs, combining retrieval (RAG), reasoning, and tool orchestration.
• You will develop multi-step intelligent systems that incorporate planning, memory, and real-world tool usage to solve complex tasks.
• You will work with MCP-style architectures (or equivalent patterns) to structure context, enable tool interoperability, and improve system reliability.
• You will contribute to systems for recommendation, classification, and forecasting, applied to large-scale, real-world datasets.
• You will help automate complex workflows and decision-making processes, delivering measurable improvements to business performance.

What They’ll Do

• You will own problems end-to-end, taking ideas from initial exploration through to production deployment and ongoing iteration.
• You will design, build, and deploy AI agents that operate reliably in real-world environments, not just prototypes or demos.
• You will integrate AI systems into products, APIs, and business processes, ensuring they are usable and scalable.
• You will work closely with engineering teams to ensure systems are robust, observable, and maintainable in production.
• You will make pragmatic decisions that balance model performance, system latency, and cost efficiency.

Core Requirements

• You have strong Python skills and can write clean, production-grade code, with a solid understanding of system design principles.
• You have proven experience shipping LLM-powered systems into production, with clear examples of real-world usage – Deployed LangChain/LangGraph solutions or similar.
• You have hands-on experience building AI agents or agentic workflows, including tool use, orchestration, and multi-step reasoning.
• You have designed and implemented RAG systems that deliver meaningful improvements, rather than simple prototypes.
• You are familiar with MCP or similar orchestration patterns, enabling structured context handling and tool integration – FastMCP/FastAPI.
• You understand LLM limitations and trade-offs, and can design systems that mitigate issues such as hallucination, latency, and cost.
• You have experience deploying systems in cloud environments (AWS, GCP, or Azure) using modern engineering practices.
• Working knowledge of SQL or data manipulation is expected, but it is not a primary focus for this role.

Profile We Want

• You have a Masters or higher background in a Mathematical/Science/Computer Science field.
• You have built, shipped, and iterated on real AI systems, and can clearly explain the decisions you made along the way.
• You demonstrate strong ownership and a bias for action, taking responsibility for outcomes rather than waiting for direction.
• You have a strong product mindset, focusing on delivering impact rather than purely optimising models.
• You are comfortable working in ambiguous, fast-moving environments, and can still deliver high-quality results.
• You are ambitious but a strong team player, contributing positively to team culture and raising the bar for others.
• For Lead or higher roles we are looking for strong mentors and can own workflows/projects end-to-end.
• Strong signals include: Experience working on SaaS or B2B AI products or delivering AI-driven transformation within an organisation.
• A background in high-growth or scaling environments, where speed and pragmatism are critical.
• Clear evidence of systems that are actively used and delivering value, rather than experimental work.

Why It’s Compelling

• You will work on AI systems that are live in production and used at scale, rather than isolated experiments.
• You will join a serious, well-supported AI build, not a side initiative or exploratory project.
• You will have high ownership and visibility, with the opportunity to influence both products and business operations.
• You will play a key role in shaping how AI is applied across a global organisation.