Senior Data Scientist - NLP AI Research

Join to apply for the Senior Data Scientist - NLP AI Research role at BBC.

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• Job band: D
  
• Contract type: Permanent, Full-time
  
• Department: BBC R&D
  
• Location: London – Hybrid, Manchester - Hybrid
  
• Proposed salary range: Up to £69,700 depending on relevant skills, knowledge and experience. The expected salary range for this role reflects internal benchmarking and external market insights.
  
• We’re also happy to discuss flexible working. If you'd like, please indicate your preference in the application – though there's no obligation to do so now. Flexible working will be part of the discussion at offer stage.
  

BBC R&D is hiring a Senior Data Scientist / Researcher to join our AI Research team, working at the forefront of AI, news and broadcasting. You’ll tackle complex, high‑impact challenges – from automated fact verification and contextual language understanding to developing editorially aligned LLMs – and see your work embedded in BBC News products, journalistic workflows and editorial decision‑making.

You’ll join a talented, collaborative group of researchers and engineers who work closely with BBC News teams and partner with leading universities, turning novel ideas into tools for journalists and programme makers at one of the world’s most respected public service broadcasters.

BBC R&D’s dedicated AI Research team is a group of 25 researchers, data scientists and engineers that explores the use of AI, principally in the areas of Natural Language Processing, Large Language Model research and Computer Vision. This team collaborates closely with other Applied Research Areas within BBC R&D, as well as teams in BBC Product, Technology, News, Archive and iPlayer. We work closely in partnership with world‑leading academic groups to help to drive innovation in the research space and accelerate the adoption of AI within the BBC.

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• Innovate and solve complex problems. Apply creative thinking and sound judgement to develop innovative solutions to technical challenges, often exploring diverse approaches.
  
• Prototype and evaluate technologies. Design, build, and test prototypes to explore research questions and assess new technologies through trials, lab tests, and user feedback.
  
• Drive impact through knowledge transfer. Translate research outcomes into practical solutions for the BBC or broader industry via operational systems, open‑source contributions, or standards input.
  
• Collaborate across and beyond the BBC. Work closely with internal teams and external partners, including universities and manufacturers, to deliver impactful results on joint projects.
  
• Communicate and represent the BBC. Share findings through internal documentation, external publications, and research conferences.
  

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• Advanced degree in a relevant field: Bachelor’s, Master’s, or Ph.D. in Machine Learning, Computer Science, or a closely related discipline.
  
• Good knowledge of modern LLM theory: Strong understanding of the theoretical foundations of large language models, including attention mechanisms and training and inference techniques (e.g. PEFT, KV‑cache, RoPE, etc.).
  
• Expertise in NLP & ML tools: Hands‑on experience with cutting‑edge NLP models (GPT family, Google Gemini, Claude, BERT) and proficiency in frameworks like PyTorch, TensorFlow, and Scikit‑Learn.
  
• Strong programming & development skills: Excellent Python coding abilities and familiarity with software engineering best practices.
  
• Applied ML & experimentation experience: Proven track record in designing experiments, building training pipelines, and translating business needs into technical solutions.
  
• Modern MLOps & cloud knowledge: Competence in cloud deployment, data management, and MLOps workflows including versioning and performance evaluation.
  

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• Hands‑on experience deploying systems to Azure and/or OpenStack, with a strong grasp of cloud‑native architectures and best practices.
  
• Proven web application development expertise, from building responsive UIs to integrating complex back‑ends.
  
• Skilled in managing and evolving large‑scale codebases, with a focus on maintainability, scalability, and clean architecture.
  
• Collaborative approach to innovation, working closely with Data Scientists, ML Engineers and researchers to translate cutting‑edge ideas into production‑ready solutions.
  
• Successful academic background, participation in published documents within your area of specialism.
  

If you can bring some of these skills and experience, along with transferable strengths, we’d love to hear from you and encourage you to apply.

Before your start date, you may need to disclose any unspent convictions or police charges, in line with our Contracts of Employment policy. This allows us to discuss any support you may need and assess any risks. Failure to disclose may result in the withdrawal of your offer.

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