Data Scientist - London

Salary: £65,000 - 105,000 per year

Requirements:

• We require a Masters or PhD in Computer Science, Data Science, Machine Learning, NLP, Information Retrieval, or a related field.
• We require experience in data science, machine learning, applied NLP, information retrieval, generative AI, or a related field.
• We require hands-on experience with LLM-based applications and generative AI systems.
• We require hands-on experience with RAG pipelines and retrieval systems.
• We require hands-on experience with search and retrieval architectures, including lexical, vector, and hybrid approaches.
• We require experience with evaluation methodologies for IR and generative AI systems.
• We require strong programming skills in Python.
• We require experience with modern AI/ML frameworks and tooling such as PyTorch, Hugging Face, LangChain, LangGraph, or Haystack.
• We require experience working with Databricks or similar distributed data and machine learning platforms.
• We require an understanding of experimentation methodologies, evaluation frameworks, and statistical analysis.
• We require proficiency with data visualization and analytical tooling such as Tableau, Power BI, matplotlib, or seaborn.
• We require demonstrated ability to independently execute technical projects and contribute to cross-functional initiatives.

Responsibilities:

• We develop and improve LLM-powered research workflows, including scientific question answering, literature summarization, semantic exploration and discovery, research insight generation, and citation-aware retrieval and reasoning workflows.
• We build and iterate on agentic and multi-step AI workflows using frameworks such as LangGraph and related orchestration tools.
• We apply modern techniques in NLP, generative AI, embeddings and semantic representations, retrieval-augmented generation, and AI reasoning and workflow orchestration.
• We evaluate emerging AI models, tools, and frameworks and contribute recommendations for experimentation and adoption.
• We contribute to prompt engineering, grounding strategies, context management, and hallucination mitigation efforts.
• We support integration of scientific metadata, ontologies, and knowledge assets into AI-powered workflows.
• We design, develop, and optimize search and retrieval pipelines, including lexical, vector, and hybrid retrieval approaches.
• We contribute to the development and enhancement of RAG systems that integrate LLMs with trusted scientific and biomedical content.
• We experiment with embeddings, re-ranking models, chunking strategies, and retrieval orchestration techniques to improve relevance and answer quality.
• We support development of semantic search, ranking, and knowledge discovery capabilities.
• We collaborate with engineering teams to deploy and scale AI-powered solutions.
• We develop and apply evaluation frameworks for search and AI systems, including IR metrics and LLM/RAG evaluation metrics.
• We build and maintain evaluation datasets, benchmark suites, and annotation workflows.
• We conduct offline experiments and contribute to online experimentation and A/B testing.
• We analyze experimental results and communicate findings to stakeholders.
• We contribute to responsible AI practices focused on quality, reliability, and trust.
• We partner with product managers, engineers, UX researchers, and domain experts to deliver AI-powered capabilities.
• We communicate technical findings and recommendations clearly to both technical and non-technical audiences.
• We contribute to knowledge sharing and adoption of best practices across the Platform Data Science organization.
• We support delivery of projects from research and experimentation through production deployment.

Technologies:

• AI
• Databricks
• Support
• LLM
• Machine Learning
• Power BI
• PyTorch
• Python
• RAG
• Tableau
• UX UI Design
• MLOps

More:

We are Elsevier, a global leader in information and analytics, helping researchers, clinicians, and life sciences professionals advance discovery and improve health outcomes through trusted content, data, and analytics. This role sits within our Platform Data Science organization, a centralized AI and data science group focused on intelligent discovery, retrieval, and generative AI capabilities across our products and platforms, including LeapSpace and our broader Search & AI Platform. We offer a comprehensive pension plan, home, office, or commuting allowance, generous vacation entitlement with sabbatical leave, maternity, paternity, adoption and family care leave, flexible working hours, a personal choice budget, internal communities and networks, employee discounts, a recruitment introduction reward, and an Employee Assistance Program. The role is based in London Wall and is full time.

last updated 36 week of 2026