Data Scientist

Data ScientistThese are full-time roles in our Philadelphia tech hub. Please do not apply if you are unable to work in Philadelphia.We are unable to transfer H1b visas currently.Have you recently obtained your Masters degree or PhD?Due to our unprecedented growth across our Data Science organization and multiple core business units, we are significantly expanding our Data Scientist team. These are not generic Data Scientist positions. As a Data Scientist on our team, you will play a key role in driving innovation across our core Health Markets products, applying advanced Data Science capabilities to meaningful business and customer challenges. These full-time employee Data Scientist positions.As part of this expansion, you will receive comprehensive training and development across the technologies and methodologies that power our Data Science organization, including NLP, Machine Learning (ML), Retrieval-Augmented Generation (RAG), and other essential Data Science capabilities. This opportunity is designed to provide both immediate impact and a strong foundation for long-term growth within our rapidly expanding Data Science organization as we have an established career track from Data Scientist up to Senior Leadership positions.In this role you willDesign and deploy machine learning, NLP, and generative AI solutions that help researchers discover, understand, and apply scientific knowledge.Build intelligent retrieval, search, recommendation, ranking, and question-answering systems that improve research outcomes.Develop AI systems that connect information across publications, datasets, citations, knowledge graphs, and scientific ontologies.Fine-tune, evaluate, and integrate large language models and retrieval-augmented generation (RAG) systems into production environments.Create robust evaluation frameworks that measure quality, reliability, relevance, trustworthiness, and user impact.Build scalable data pipelines and machine learning workflows that support experimentation, monitoring, and continuous improvement.Apply the appropriate combination of classical machine learning, deep learning, retrieval, and generative AI techniques to solve complex scientific problems.Collaborate with engineering, product, UX, analytics, and domain experts to transform ambiguous challenges into practical solutions.RequirementsDegree in Data Science, Machine Learning, Artificial Intelligence, Computer Science, Statistics, Applied Mathematics, or a related quantitative discipline.Extensive Python programming skills and experience building production-quality data science solutions.Experience with machine learning fundamentals, including model development, evaluation, feature engineering, and performance optimization.Must be able to work in Philadelphia.Must not require visa assistanceAbout ElsevierElsevier employs approximately 10,000 people worldwide, including more than 2,500 technologists, and has supported researchers and healthcare professionals for more than 140 years. Today, Elsevier combines deep domain expertise with technology, data, analytics, and AI to create solutions that help advance science, improve healthcare, and drive better outcomes.For Data Scientists, one of the most exciting areas of growth is our Health Markets business, where we are applying data science, machine learning, and generative AI to transform how healthcare professionals access and use clinical knowledge. Products such as ClinicalKey and ClinicalKey AI bring together Elsevier's extensive medical content, clinical expertise, and advanced AI capabilities to help healthcare professionals find relevant, trusted information and make more informed clinical decisions.Our Data Science teams work across a broad range of challenges, including machine learning, predictive analytics, natural language processing, information retrieval, generative AI, large language models, and retrieval-augmented generation (RAG). These capabilities are being incorporated into products that serve clinicians, researchers, educators, and healthcare organizations around the world.