Senior Data Scientist I

Senior Data Scientist I Are you interested in working with data and analytics to solve problems? Are you interested in bringing your Gen AI, Machine Learning and NLP expertise to projects?

About our Team:- Data Science Global Operations team works with a focus on Generative AI, Machine Learning, Natural Language Processing, and Statistical techniques. It helps in building state of the art applications in customer experience, process innovation, content processing to drive efficiency across global operations in Elsevier. A Senior Data Scientist will play a pivotal role in the development and deployment of cutting-edge Generative AI models and solutions.

About the Role:- They will act as a consultant to the Clinical Solutions (CS) team, partnering on various diverse use cases and assessing the right technical fit for each use case — whether an AI-tool-based solution (e.g., Claude, Chat GPT) or a more traditional pipeline-based approach best fits the requirements, cost, and scale involved. They will be responsible for building, testing, and maintaining our Generative AI, Retrieval Augmented Generation (RAG) and Natural Language Processing (NLP) solutions. This includes evaluating their performance and implementing guardrails to ensure ethical and responsible use of AI technologies. They will engage in the entire life cycle of data science projects, including design, implementation, evaluation, productionisation and ongoing enhancement.

Responsibilities:-A key focus of the work will be on the customization and optimization of existing RAG pipelines to support applications that involve content ingestion, machine translation, and contextualized information retrieval. Experience with end-to-end model deployment, including leveraging AI agents, Model Context Protocol (MCP) for effective context management, and cloud platforms such as AWS (including AWS Bedrock), Azure, or similar services, is a strong plus. Their deliverables will include efficient, production-ready Python code, with experience in Java considered an asset. They will collaborate closely with Subject Matter Experts (SMEs) and the technology team to deploy and operationalize our data science pipelines.