Data Scientist – Generative AI

Argus is where smart people belong and where they can grow. We answer the challenge of illuminating markets and shaping new futures.What we're looking forJoin our Generative AI team to help shape how AI is used across Argus.We are looking for a Data Scientist with hands-on experience developing Generative AI applications. Working alongside other data scientists and engineers, you will help develop customer-facing GenAI solutions and the data capabilities that underpin them.A key initial focus will be helping make Argus content and data AI-ready, and developing the retrieval, evaluation and agentic capabilities needed to use that data effectively in AI-powered products.You will also contribute to the wider development of GenAI capabilities as our technology and use cases evolve.What will you be doing?As part of a multidisciplinary GenAI team, you will:Customer-facing GenAI: Help develop and improve GenAI capabilities used in Argus products, combining LLMs, retrieval, data and agentic approaches to solve real customer problems.AI-Ready Data: Transform, enrich and structure Argus content and data so that it can be effectively understood and used by AI systems.Search & Retrieval: Develop and improve semantic, vector and hybrid retrieval capabilities across Argus content and data.Agent Development: Develop agentic applications and workflows using LangChain and LangGraph, combining tools, retrieval and LLM reasoning.Agent Tooling: Help develop APIs, MCP tools and other reusable capabilities that allow AI agents to interact reliably with data and services.Evaluation & Optimisation: Evaluate and improve the quality and reliability of GenAI systems, including retrieval, tools and agent behaviour.Technical Delivery: Develop high-quality Python components, services and data pipelines, applying good software engineering practices.Collaboration: Work closely with data scientists, engineers, editorial, product and business teams to develop scalable GenAI solutions.Skills and ExperienceStrong Python skills, with hands-on experience developing Generative AI applications.Practical experience using LangChain and/or LangGraph to build LLM-powered applications or agentic workflows.Practical experience with RAG, semantic search, embeddings, vector databases and modern retrieval techniques.Experience integrating LLMs with data, tools or external services.Experience working with and preparing structured or unstructured data for effective use by AI systems.An understanding of approaches for evaluating and improving LLM, retrieval or agentic systems.Practical experience with cloud platforms such as Azure, AWS or Google Cloud and technologies such as Docker.Strong problem-solving, communication and collaboration skills.Experience with Model Context Protocol (MCP), GraphRAG or knowledge graph-based retrieval, entity resolution or LLM evaluation would be an advantage.