at the forefront of applied research in an industry setting? Thomson Reuters Labs in London s seeking scientists with a passion for solving problems using state-of-the-art informationretrieval, natural language processing and generative AI. What does Thomson Reuters Labs do? We experiment, we build, we deliver. We support the organization and our customers through applied … research in informational retrieval and natural language processing. We work closely with product and domain experts to identify compelling solutions at the intersection of user need and technical feasibility. Our team is designing the next generation of search technology for Legal and Tax Professionals globally. We drive AI innovation for Thomson Reuters' Core Research Products, including Westlaw , Practical Law … About the Role Lead Applied Scientists are experts in Machine Learning/NLP, responsible for the design and delivery of AI solutions that enhance Thomson Reuters' products. They leverage informationretrieval techniques, prompting workflows, model training and evaluation design to build and optimize solutions. Their work ensures AI technologies are effectively aligned with business objectives, driving product innovation More ❯
blends advanced modeling, analytical investigations and project ownership. You'll take the lead on projects that improve the core discovery experience-such as personalisation, relevance ranking, and multi-modal retrieval-as well as conduct deep investigations into user behaviour and feature performance. You'll be working across the full research and experimentation lifecycle: from framing the problem and exploring … launch Conduct statistical investigations into customer behaviour and funnel performance (e.g. search abandonment, filter usage, session patterns) Run literature reviews and research spikes on emerging techniques-e.g. LLM-assisted retrieval, hybrid recommenders, contrastive learning Collaborate with ML engineers to move promising prototypes into production Design and analyse AB tests to evaluate impact on discovery metrics (e.g. conversion, engagement, retention … or user modelling Strong Python and SQL skills, with deep experience in data exploration, feature engineering and model evaluation Proven experience applying and comparing models for structured prediction, ranking, retrieval or recommendation Strong understanding of offline evaluation techniques and trade-offs in informationretrieval and recommender systems Ability to communicate clearly across disciplines and seniority levels-including More ❯
orchestration. You have hands-on experience with LLM APIs (OpenAI, Anthropic, etc.) and orchestration frameworks like LangChain, LlamaIndex, or have built custom agent frameworks from scratch. You understand intelligent information retrieval. You have experience with RAG (Retrieval-Augmented Generation) systems, vector databases, and embedding models for knowledge extraction. You can architect complex workflows. You have experience with workflow More ❯
d love to hear from you and encourage you to apply. Strong understanding and experience of development and productionisation of data science products in the Search domain, for example, information retrieval. Strong understanding and experience of experimentation within data science. Experience with model lifecycle management and MLOps, particularly within AWS. Experience of supporting other Data Scientist/s with … means for those employees seeking redeployment their application will be considered alongside anyone else at risk of redundancy, prior to any individuals being considered who are not at risk. Information at a Glance This is your BBC At the BBC you can create and innovate in an inclusive environment while contributing to some of the world's best loved More ❯
