> Markdown version of [/jobs/ext/3881017-senior-data-scientist-i-leapspace](https://www.wearedevelopers.com/jobs/ext/3881017-senior-data-scientist-i-leapspace). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Scientist I - LeapSpace - **Company:** Elsevier Inc. - **Location:** London, UK - **Experience:** Expert - **Salary:** £69,610.0 - **Contract:** Permanent contract - **Skills:** LangGraph Framework, AI Evaluation, A/B Testing, Artificial Intelligence, Automated Storage and Retrieval Systems, Computer Programming, Data Visualization, Distributed Data Store, Graph Database, Information Retrieval, Python (Programming Language), Machine Learning, Natural Language Processing, Recommender Systems, Power BI, Tensorflow, Azure Machine Learning, Search Technologies, Tableau (Software), Haystack, Normalized Discounted Cumulative Gain, Pytorch, LangChain, Retrieval-Augmented Generation, Large Language Models, Prompt Engineering, Generative AI, Agentic-AI, Matplotlib, Information Technology, HuggingFace, Machine Learning Operations, Automation Anywhere, Databricks - **Published:** October 23, 2026 - **Apply:** https://www.adzuna.co.uk/jobs/details/5939034278 ## About the Role This role is ideal for someone with strong hands-on experience in applied AI, NLP, retrieval systems, and LLM-based applications, who enjoys rapidly prototyping and translating emerging AI techniques into scalable product capabilities., * Master's or PhD in Computer Science, Data Science, Machine Learning, NLP, Information Retrieval, or a related field * Significant experience in applied AI, machine learning, NLP, or information retrieval * Strong hands-on experience with: + LLM-based applications and generative AI systems + RAG pipelines and retrieval systems + Search and retrieval architectures (lexical, vector, hybrid) + Evaluation methodologies for IR and generative AI systems * Advanced programming skills in Python * Experience with modern AI/ML frameworks and tooling (e.g., PyTorch, Hugging Face, LangChain, LangGraph, Haystack) * Experience working with Databricks or similar distributed data/ML platforms * Strong understanding of experimentation design, evaluation frameworks, and statistical analysis * Proficiency with data visualization and analytical tooling (e.g., Tableau, Power BI, matplotlib, seaborn), * Experience building AI assistants, agentic workflows, or conversational AI systems * Experience working on large-scale search, ranking, or recommendation systems * Familiarity with scientific, biomedical, or scholarly datasets * Experience with knowledge graphs, ontologies, or semantic enrichment systems * Exposure to production ML systems and MLOps practices * Publications or applied research contributions in NLP, IR, search, or generative AI * Experience building AI systems in regulated, high-trust, or content-rich domains ## Description About the role: We are looking for a Senior Data Scientist I to help design, build, and evaluate advanced AI capabilities powering LeapSpace. This role will focus heavily on applied AI research and development, including prototyping intelligent workflows, integrating large language models with trusted scientific data, and advancing AI-assisted research experiences. You will work across retrieval systems, generative AI, reasoning workflows, evaluation frameworks, and AI experimentation, helping shape the future of AI-powered scientific discovery at Elsevier., Applied AI & Research * Lead prototyping and development of LLM-powered research workflows, including: + Scientific question answering + Literature summarization + Semantic exploration and discovery + Research insight generation + Citation-aware reasoning workflows * Design and iterate on agentic and multi-step AI workflows using frameworks such as LangGraph and related orchestration tooling. * Apply state-of-the-art techniques in: + NLP + Generative AI + Embeddings and semantic representations + Retrieval-augmented generation (RAG) + AI reasoning and orchestration * Rapidly evaluate emerging AI models, tooling, and frameworks to identify opportunities for product innovation. * Translate applied AI research into scalable, production-oriented solutions that improve researcher productivity and trust. * Contribute to experimentation around prompt engineering, context management, grounding strategies, and hallucination mitigation. * Support integration of scientific metadata, ontologies, and knowledge assets into AI workflows. Search, Retrieval & RAG Systems * Design and optimize search and retrieval pipelines, including lexical, vector, and hybrid retrieval approaches. * Develop and improve RAG systems that integrate LLMs with trusted scientific and biomedical content. * Experiment with embeddings, re-ranking models, chunking strategies, and retrieval orchestration to improve relevance and answer quality. * Build scalable workflows for semantic search and knowledge discovery. * Collaborate closely with engineering teams to productionize AI and retrieval systems. AI Evaluation & Experimentation * Develop and evolve evaluation frameworks for search and AI systems, including: + IR metrics (e.g., NDCG, recall, precision) + LLM and RAG evaluation metrics (e.g., grounding, faithfulness, hallucination detection) * Design offline evaluation methodologies and contribute to online experimentation and A/B testing. * Build and maintain evaluation datasets, benchmark suites, and annotation strategies. * Drive rigorous experimentation to measure system improvements and user impact. * Contribute to responsible AI practices, including quality, reliability, and trust evaluation. Cross-functional Leadership * Partner with product managers, engineers, UX researchers, and domain experts to deliver impactful AI capabilities. * Translate complex technical findings into actionable recommendations for stakeholders. * Contribute to technical strategy and roadmap discussions for LeapSpace AI capabilities.