Data Scientist - GenAI - London

Job Title: Data Scientist (Contract) Location: London - Hybrid (occasional travel to the London office) Duration: 6 months Start Date: ASAP 2025 Overview An opportunity has arisen for an experienced Data Scientist to join a leading Data and AI Team, supporting digital transformation projects across Tax and Legal. This role involves designing and developing Generative AI and Machine Learning (ML) solutions using Python and Microsoft Azure. You'll work with cross-functional teams to build intelligent, data-driven applications that solve complex business challenges and deliver measurable impact. Key Responsibilities • Design, build, and deploy Python-based AI and ML applications. • Research and develop new Generative AI techniques, including fine-tuning and prompt engineering. • Develop and maintain LLM-assisted frameworks and automation pipelines. • Write clean, maintainable, and well-documented code for scalable deployment. • Build and implement testing and evaluation frameworks for AI models. • Collaborate with data scientists, software engineers, and subject-matter experts to deliver innovative solutions. Essential Skills & Experience • Advanced Python programming skills with hands-on experience using NumPy, Pandas, Scikit-learn, Langchain, LlamaIndex, and Azure AI Foundry. • Proven experience working with Azure cloud services and Generative AI R&D. • Strong understanding of machine learning, data modelling, and natural language processing (NLP) techniques. • Experience with fine-tuning, prompt orchestration, and retrieval methods (RAG, knowledge graphs). • Familiarity with frameworks such as LangGraph, Azure AI Foundry Agents, and Semantic Kernel Agents. • Good understanding of software engineering best practices, including version control, testing, and CI/CD. Desirable Skills • Experience creating optimised data workflows and scalable AI solutions. • Deep understanding of Microsoft Azure AI services. • Strong data analytics and visualisation skills using Excel and Alteryx. • Awareness of Responsible AI and ethical model design principles.