Data Scientist III - LeapSpace

Elsevier; City Of London; On-site; GBP 80,000 - 120,000; Full time

Benefits offered by this job

Pension plan

Commuting allowance

Vacation entitlement

Family leave

Flexible hours

Personal budget

Employee networks

Discount programs

Referral bonus

EAP

Job summary

Elsevier is seeking a senior Platform Data Scientist to advance intelligent discovery, retrieval, and generative AI across Elsevier products. You will design and iteratively improve LLM-powered research workflows, from scientific question answering to literature summarization, with a focus on grounding and reliable outputs.

Collaborate with product managers and engineers to deploy AI solutions, evaluate models, and integrate scientific metadata and ontologies.

Qualifications

• 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
• 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
• Strong 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 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

Responsibilities

• Develop and improve LLM-powered research workflows, including: Scientific question answering, literature summarization, semantic exploration and discovery
• Build and iterate on agentic and multi-step AI workflows using frameworks like LangGraph and related orchestration tools
• Apply modern techniques in NLP, Generative AI, embeddings and semantic representations, retrieval-augmented generation (RAG) and AI reasoning
• Evaluate emerging AI models, tools, and frameworks and contribute recommendations for experimentation and adoption
• Contribute to prompt engineering, grounding strategies, context management, and hallucination mitigation efforts
• Support integration of scientific metadata, ontologies, and knowledge assets into AI-powered workflows
• Design, develop, and optimize search and retrieval pipelines (lexical, vector, hybrid)
• Collaborate with engineering teams to deploy and scale AI-powered solutions

Skills

Python

LLM development

NLP

Data science

Experimentation

Education

Master's or PhD in Computer Science, Data Science, ML, NLP, IR, or related field

Tools

PyTorch

Hugging Face

LangChain

LangGraph

Haystack

Databricks

Job description

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.

About the role

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 and AI Platform.

Key responsibilities

Applied AI & Research

• Develop and improve LLM-powered research workflows, including: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.
• Apply modern techniques in: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.
• Contribute to prompt engineering, grounding strategies, context management, and hallucination mitigation efforts.
• Support integration of scientific metadata, ontologies, and knowledge assets into AI-powered workflows.

Search, Retrieval & RAG Systems

• 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.
• Support development of semantic search, ranking, and knowledge discovery capabilities.
• 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:IR metrics (e.g., NDCG, recall, precision)LLM and RAG evaluation metrics (e.g., grounding, faithfulness, hallucination detection)
• Build and maintain evaluation datasets, benchmark suites, and annotation workflows.
• Conduct offline experiments and contribute to online experimentation and A/B testing.
• Analyze experimental results and communicate findings to stakeholders.
• Contribute to responsible AI practices focused on quality, reliability, and trust.

Cross-functional Collaboration

• Partner with product managers, engineers, UX researchers, and domain experts to deliver AI-powered capabilities.
• Communicate technical findings and recommendations clearly to both technical and non-technical audiences.
• 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.

Required qualifications

• 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
• Hands-on experience with: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., PyTorch, Hugging Face, LangChain, LangGraph, Haystack)
• 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

Preferred qualifications

• Experience building AI assistants, agentic workflows, or conversational AI applications
• Experience working on search, ranking, recommendation, or retrieval 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
• Academic or industry research experience in NLP, information retrieval, search, or generative AI
• Experience working in content-rich, knowledge-intensive, or highly regulated domains

Working for you

We know that your well-being and happiness are key to a long and successful career. These are some of the benefits we are delighted to offer:

• 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
• Personal Choice budget
• Internal communities and networks
• Various employee discounts
• Recruitment introduction reward
• Employee Assistance Program (global)

About the business

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. At Elsevier, your work contributes to the world’s grand challenges and a more sustainable future. We harness innovative technologies to support science and healthcare to partner for a better world.

We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits.

We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law.

We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-855-833-5120.