About the team Elsevier’s mission is to help researchers, clinicians, and life sciences professionals advance discovery and improve health outcomes through trusted content, data, and analytics. This role sits within Elsevier’s Platform Data Science organization , a centralized AI and data science group responsible for advancing intelligent discovery, retrieval, and generative AI capabilities across Elsevier products and platforms. The organization develops foundational AI technologies that power experiences such as LeapSpace , Elsevier’s AI-powered research assistant, as well as Elsevier’s broader Search & AI Platform . The Platform Data Science organization works at the intersection of: Generative AI and LLM applications AI evaluation and experimentation Scalable AI platforms and intelligent workflows We are looking for a Data Scientist III to help design, build, and evaluate advanced AI capabilities supporting LeapSpace and Elsevier’s Search & AI Platform initiatives. This role focuses on applied AI development, retrieval systems, and AI evaluation , helping bring cutting-edge AI technologies into production experiences used by researchers worldwide. You will work closely with senior data scientists, engineers, product managers, and domain experts across retrieval systems, generative AI, reasoning workflows, evaluation frameworks, and experimentation , contributing to the next generation of AI-powered scientific discovery tools. This role is ideal for someone with hands-on experience in applied AI, NLP, information retrieval, and LLM-based applications , who enjoys building innovative solutions and translating emerging AI techniques into impactful product capabilities. Applied AI & Research Scientific question answeringLiterature summarizationSemantic exploration and discoveryResearch insight generationCitation-aware retrieval and reasoning workflows Build and iterate on agentic and multi-step AI workflows using frameworks such as LangGraph and related orchestration tools. NLPGenerative AIEmbeddings and semantic representationsRetrieval-augmented generation (RAG)AI reasoning and workflow orchestration Evaluate emerging AI models, tools, and frameworks and contribute recommendations for experimentation and adoption. Support integration of scientific metadata, ontologies, and knowledge assets into AI-powered workflows. Design, develop, and optimize search and retrieval pipelines , including lexical, vector, and hybrid retrieval approaches. Contribute to the development and enhancement of RAG systems that integrate LLMs with trusted scientific and biomedical content. Experiment with embeddings, re-ranking models, chunking strategies, and retrieval orchestration techniques to improve relevance and answer quality. Collaborate with engineering teams to deploy and scale AI-powered solutions. AI Evaluation & Experimentation Develop and apply evaluation frameworks for search and AI systems, including:Conduct offline experiments and contribute to online experimentation and A/B testing. Contribute to responsible AI practices focused on quality, reliability, and trust. Partner with product managers, engineers, UX researchers, and domain experts to deliver AI-powered capabilities. Contribute to knowledge sharing and adoption of best practices across the Platform Data Science organization. Support delivery of projects from research and experimentation through production deployment. Batchelor's, Master’s or PhD in Computer Science, Data Science, Machine Learning, NLP, Information Retrieval, or a related field Experience in data science, machine learning, applied NLP, information retrieval, generative AI, or a related field LLM-based applications and generative AI systemsRAG pipelines and retrieval systemsSearch and retrieval architectures (lexical, vector, hybrid) Evaluation methodologies for IR and generative AI systems Strong programming skills in Python Experience with modern AI/ML frameworks and tooling (e.g., Experience working with Databricks or similar distributed data and machine learning platforms Understanding of experimentation methodologies, evaluation frameworks, and statistical analysis Proficiency with data visualization and analytical tooling (e.g., Tableau, Power BI, matplotlib, seaborn) Demonstrated ability to independently execute technical projects and contribute to cross-functional initiatives Experience building AI assistants, agentic workflows, or conversational AI applications Familiarity with scientific, biomedical, or scholarly datasets Exposure to production ML systems and MLOps practices Academic or industry research experience in NLP, information retrieval, search, or generative AI Experience working in content-rich, knowledge-intensive, or highly regulated domains Comprehensive Pension Plan Home, office, or commuting allowance. Generous vacation entitlement and option for sabbatical leave Maternity, Paternity, Adoption and Family Care leave Flexible working hours Internal communities and networks Various employee discounts Employee Assistance Program (global) As a global leader in information and analytics, we help researchers and healthcare professionals advance science and improve health outcomes for the benefit of society. Building on our publishing heritage, we combine quality information and vast data sets with analytics to support visionary science and research, health education, and interactive learning, as well as exceptional healthcare and clinical practice.
Data Scientist Ml Ai Python in London employer: Elsevier
At Elsevier, we pride ourselves on being an excellent employer, particularly for our Java Software Engineer role in Oxford. Our vibrant work culture fosters collaboration and innovation, while our commitment to employee growth is evident through continuous learning opportunities and flexible working arrangements that promote a healthy work-life balance. Join us to be part of a team that values your contributions and supports your professional journey in the exciting field of scientific knowledge sharing.
