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About the Role

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.

Responsibilities

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.
Build and iterate on agentic and multi-step AI workflows using frameworks such as LangGraph and related orchestration tools.
Apply modern techniques in NLP, Generative AI, Embeddings and semantic representations, Retrieval-Augmented Generation (RAG), and 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.
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.
Develop and apply evaluation frameworks for search and AI systems, including IR metrics (e.g., NDCG, recall, precision) and 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.
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.

Requirements

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), and 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

Skills

Applied AI
NLP
Information Retrieval
LLM-based applications
Generative AI
Embeddings
Semantic representations
Retrieval-augmented generation (RAG)
AI reasoning
Workflow orchestration
Prompt engineering
Grounding strategies
Context management
Hallucination mitigation
Search and retrieval pipelines
Lexical retrieval
Vector retrieval
Hybrid retrieval
Embeddings
Re-ranking models
Chunking strategies
Retrieval orchestration
Semantic search
Ranking
Knowledge discovery
IR metrics
LLM evaluation metrics
RAG evaluation metrics
Evaluation datasets
Benchmark suites
Annotation workflows
Offline experiments
Online experimentation
A/B testing
Responsible AI practices
Python
PyTorch
Hugging Face
LangChain
LangGraph
Haystack
Databricks
Data visualization
Tableau
Power BI
matplotlib
seaborn

Location

Remote

Work Type

Full-time

Experience Level

Data Scientist III

Education Level

Master’s or PhD in Computer Science, Data Science, Machine Learning, NLP, Information Retrieval, or a related field

Benefits

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 Company

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: Search and retrieval systems, Generative AI and LLM applications, AI evaluation and experimentation, Semantic enrichment and knowledge systems, Scalable AI platforms and intelligent workflows.
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.

Equal Opportunity

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.
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.
USA Job Seekers: EEO Know Your Rights.