Data Scientist

Overview As a Data Scientist at Elsevier, you design, deploy, and E2E AI/ML solutions to accelerate scientific discovery. You work with a rich corpus of publications, datasets, and knowledge graphs to make knowledge more discoverable and trustworthy. You will build systems for retrieval, search, and question-answering, and couple AI with real-world impact across research, healthcare, and education. This role combines cutting-edge AI with meaningful outcomes and collaboration with cross-functional teams. Compensation / Benefitsannual incentive bonuscountry-specific benefits ResponsibilitiesDesign and deploy ML, NLP, and generative AI solutions to help researchers discover and apply knowledgeBuild intelligent retrieval, search, recommendation, ranking, and QA systemsDevelop AI systems connecting publications, datasets, citations, knowledge graphs, and ontologiesFine-tune and integrate large language models and RAG into productionCreate robust evaluation frameworks for quality, reliability, relevance, and impactBuild scalable data pipelines and ML workflows for experimentation and monitoringApply classical ML, deep learning, retrieval, and generative AI techniques to scientific problemsCollaborate with engineering, product, UX, analytics, and domain experts to translate challenges into solutionsDeliver clean, maintainable production-ready Python code and reusable AI componentsContinuously improve AI capabilities and real-world value of discovery systems Key requirementsDegree in data science, ML, AI, CS, statistics, applied mathematics, or related quantitative disciplineExtensive Python programming and production-quality DS experienceML fundamentals including model development, evaluation, feature engineering, and optimizationExperience with large-scale structured, semi-structured, or unstructured dataHands-on with modern AI tech: LLMs, embeddings, retrieval, generative AIFamiliarity with Scikit-learn, PyTorch, TensorFlow, Hugging Face, or equivalentsExperience evaluating AI outputs and improving model quality, reliability, and business impactAbility to translate complex problems into data-driven solutionsGenuine passion for advancing science and real-world impactcollaboration across functionsclear communicationproblem framing and critical thinkingPythonMachine LearningNLP