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About the Role

Design and build machine learning, NLP, and generative AI solutions that support scientific discovery, knowledge extraction, decision support, and intelligent content understanding. Work with large-scale scientific content and data, applying the right techniques to solve complex problems and deliver reliable, production-ready systems. Collaborate with cross-functional partners to turn ambiguous challenges into measurable outcomes that improve how researchers discover and use knowledge.

Responsibilities

Design and build machine learning, NLP, and generative AI systems for scientific discovery, knowledge extraction, decision support, and intelligent content understanding.
Work with large-scale, complex, and heterogeneous data, including scientific publications, research datasets, knowledge graphs, ontologies, taxonomies, citations, metadata, and content from every scientific discipline.
Apply the right technique to each problem, using approaches such as classification, regression, clustering, ranking, feature engineering, deep learning, embeddings, LLMs, retrieval, and generative AI.
Develop capabilities for semantic search, information retrieval, entity extraction, content classification, recommendation, ranking, summarization, question answering, and evidence-grounded generation.
Build, evaluate, fine-tune, prompt, and integrate models into robust production systems, while continuously improving quality, relevance, reliability, and user value.
Write clean, tested, production-quality Python and contribute reusable data science components, packages, and scalable data pipelines for preprocessing, inference, experimentation, monitoring, and continuous improvement.
Support deployment, monitoring, model maintenance, drift detection, automated retraining, and ongoing optimization of data science systems.
Collaborate with engineering, product, UX, analytics, research, and domain experts, and communicate technical concepts, model behavior, insights, trade-offs, and recommendations clearly to technical and non-technical audiences.

Requirements

Experience in data science, machine learning, artificial intelligence, NLP, statistics, applied mathematics, computer science, or a related quantitative area.
Experience working with frontier LLMs such as OpenAI’s GPTs, Anthropic’s Claude, and Google’s Gemini, including fine-tuning LLMs and/or SLMs.
Strong Python skills and a habit of writing clean, maintainable, well-tested code.
A solid grasp of machine learning fundamentals, including supervised and unsupervised learning, feature engineering, model evaluation, model selection, and performance measurement.
Experience working with structured, semi-structured, or unstructured data, especially large-scale text or content datasets.
Familiarity with common data science and machine learning tools such as Pandas, NumPy, SciPy, Scikit-learn, PyTorch, TensorFlow, or Matplotlib.
The ability to translate complex and ambiguous requirements into practical, measurable, data-driven solutions, with strong analytical thinking, problem-solving skills, and attention to quality.
Clear communication skills, a collaborative approach to working with engineering, product, and business stakeholders, and a genuine interest in building production-ready systems that deliver real user value.

Skills

Machine Learning
NLP
Generative AI
Python
Data Science
Artificial Intelligence
Statistics
Applied Mathematics
Computer Science
LLMs
Pandas
NumPy
SciPy
Scikit-learn
PyTorch
TensorFlow
Matplotlib

Work Type

Flexible hours

Benefits

Wellbeing initiatives
Shared parental leave
Study assistance
Sabbaticals
Country specific benefits

About the Company

Elsevier is 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, vast datasets, advanced analytics, and innovative technologies to support visionary science and research, health education, interactive learning, and exceptional healthcare and clinical practice.
At Elsevier, your work contributes to the world’s grand challenges and a more sustainable future.
We harness technology to support science and healthcare in partnership with the communities we serve.
Together, we create possibilities.
RELX is a global provider of information-based analytics and decision tools for professional and business customers, enabling them to make better decisions, get better results and be more productive.
Our purpose is to benefit society by developing products that help researchers advance scientific knowledge; doctors and nurses improve the lives of patients; lawyers promote the rule of law and achieve justice and fair results for their clients; businesses and governments prevent fraud; consumers access financial services and get fair prices on insurance; and customers learn about markets and complete transactions.
Our purpose guides our actions beyond the products that we develop.
It defines us as a company.
Every day across RELX our employees are inspired to undertake initiatives that make unique contributions to society and the communities in which we operate.

Equal Opportunity

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.