Data Scientist II – Machine Learning, NLP & Generative AI

About the role

We are looking for a Data Scientist II to design and deliver machine‑learning, NLP and generative‑AI solutions that accelerate scientific discovery and improve decision‑making for researchers. The role is hybrid, based in London or Oxford, and works with large‑scale scientific content across many disciplines.

Key responsibilities

• Design and build production‑ready ML, NLP and generative‑AI systems for knowledge extraction, decision support and intelligent content understanding.
• Process heterogeneous data sources such as publications, datasets, knowledge graphs, ontologies, citations and metadata.
• Apply techniques including classification, regression, clustering, ranking, feature engineering, deep learning, embeddings, LLMs, retrieval and generative models.
• Develop capabilities for semantic search, entity extraction, content classification, recommendation, summarisation and question answering.
• Write clean, tested Python code and create reusable data‑science components, pipelines and monitoring tools.
• Support model deployment, drift detection, automated retraining and ongoing optimisation.
• Collaborate with engineering, product, UX, analytics and domain experts, communicating insights and trade‑offs to both technical and non‑technical audiences.

Required profile

• Experience in data science, machine learning, AI, NLP, statistics, applied mathematics, computer science or a related quantitative field.
• Proven ability to turn ambiguous scientific problems into measurable, production‑grade solutions.

Required skills

• Python programming
• Machine learning and deep learning
• Natural language processing (NLP)
• Generative AI and large language models (LLMs)
• Embeddings and vector retrieval
• Classification, regression, clustering, ranking
• Feature engineering
• Semantic search and information retrieval
• Entity extraction, content classification, recommendation systems
• Summarisation and question answering
• Model deployment, monitoring, drift detection, automated retraining