Senior AI Scientist — NLP, LLMs & RAG (Hybrid UK)

Elsevier; Slough; Hybrid; GBP 90,000 - 120,000; Full time

Benefits offered by this job

Shared parental leave

Study assistance

Sabbaticals

Job summary

Elsevier is hiring a Senior Data Scientist to design and deliver advanced AI, NLP, and generative AI solutions that power knowledge discovery and decision support. You will work with large scientific datasets, apply LLM-based approaches, and collaborate across teams to produce production-ready systems with measurable user impact.

The role emphasizes robust evaluation, scalable architecture, and mentorship to help the team deliver high-quality results in a hybrid London/Oxford setting.

Qualifications

• Practical experience in data science, AI, ML, NLP, information retrieval, or related quantitative field.
• Hands-on experience building AI/ML and NLP solutions in product-focused environments.
• Expertise with LLMs, fine-tuning, prompts, grounding, and responsible AI practices.
• Strong Python skills and fundamentals in machine learning.

Responsibilities

• Design, build, and evaluate advanced AI/ML, NLP, and generative AI solutions for knowledge discovery.
• Develop LLM-powered workflows and RAG systems for search, summarization, QA, and evidence-grounded insights.
• Build intelligent retrieval, ranking, recommendation, and decision-support capabilities.
• Integrate scientific metadata and ontologies into scalable AI workflows.
• Establish evaluation, experimentation, and monitoring frameworks for quality and reliability.
• Write production-ready Python code and deploy solutions at scale.
• Provide technical leadership and mentoring to ensure high-quality delivery.

Skills

AI/ML

NLP

Information retrieval

Python

LLMs

RAG workflows

Cloud platforms

Job description

Elsevier is hiring a Senior Data Scientist to design and deliver advanced AI, NLP, and generative AI solutions that power knowledge discovery and decision support. You will work with large scientific datasets, apply LLM-based approaches, and collaborate across teams to produce production-ready systems with measurable user impact.

The role emphasizes robust evaluation, scalable architecture, and mentorship to help the team deliver high-quality results in a hybrid London/Oxford setting.