Are you interested in working with data and analytics to solve problems?


Are you interested in bringing your GenAI, Machine Learning and NLP expertise to projects?


About our Team

Data Science Health Content 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 for the health sciences domain.


About the Role

As a Senior Data Scientist, you will play a pivotal role in the development and deployment of cutting-edge Generative AI models and solutions. You 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. You will engage in the entire life cycle of data science projects, including design, implementation, evaluation, productionisation and ongoing enhancement. A key focus of your 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. Your deliverables will include efficient, production-ready Python code, with experience in Java considered an asset. You will collaborate closely with Subject Matter Experts (SMEs) and the technology team to deploy and operationalize our data science pipelines.

This role requires a strong foundation in Natural Language Processing (NLP), Machine Learning, Transformer models and Generative AI, as well as proficiency in Python.

Responsibilities

Collect data, perform data analysis, develop models, define quality metrics, and conduct quality assessments of models, along with regular presentations to stakeholders.Create production-ready Python packages for each component of data science pipelines (e.g., pre-processing, model inference, evaluation) and coordinate their deployment with the technology team.Design, develop, and deploy Generative AI models and solutions that meet specific business needs.Expertise in Retrieval Augmented Generation (RAG) optimization and customization of existing RAG pipelines to meet specific project needs.Proficiency in large-scale data ingestion, preprocessing, and transformation of multilingual content to ensure high-quality inputs for downstream models.Build AI Agentic models with RAG pipeline. Fine-tune large language models (LLMs) and transformer models to enhance accuracy and relevance.Implement guardrails and evaluation mechanisms to ensure responsible and ethical AI usage.Conduct rigorous testing and evaluation of AI models to ensure high performance and reliability.Integrate data science components and ensure end-to-end quality assessment.Maintain the robustness of data science pipelines against model drift and ensure consistent output quality.Establish a reporting process for pipeline performance and develop automatic re-training strategies for existing pipelines.Work collaboratively with cross-functional teams to integrate AI solutions into existing products and services.Mentor junior data scientists and contribute to the knowledge-sharing culture within the team.Stay up-to-date with the latest advancements in AI, machine learning, and NLP technologies.


Requirements


Master’s or Ph.D. in Computer Science, Data Science, Artificial Intelligence, or a related field.7+ years of relevant applied experience in data science, with a focus on Generative AI, NLP, and machine learning.Proficiency in Python for data analysis, model development, and deployment.Strong experience with transformer models and fine-tuning techniques for large language models (LLMs).Proficiency in Generative AI technologies, including utilizing LLMs via API access, LLM evaluation tools, and prompt engineering.Knowledge of various RAG pipelines and their practical implementation.Experience building Agentic RAG systems is strong requirement.Experience with AI agent management frameworks such as LangChain, AutoGen, Haystack, MCP, or similar tools.Experience with advanced algorithms in deep learning, neural networks, reinforcement learning, and transfer learning.Familiarity with traditional machine learning algorithms such as random forests, SVM, logistic regression, and Bayesian modelling for model building, validation, and testing.Understanding of AI ethics, guardrail implementation, and evaluation metrics.Familiarity with cloud platforms (e.g., Bedrock, AWS, Azure) for model deployment and the creation of production-ready pipelines.Proficiency in data visualization tools and techniques.Experience with version control systems (e.g., GitLab or GitHub), Jira, and working in an Agile environment.Proficient in using *nix systems, open-source software, Jupyter Notebook, libraries, and cloud computing.Excellent problem-solving and analytical skills, with strong attention to detail.Strong communication skills and the ability to work effectively in a team-oriented environment.

Work in a way that works for you
 

We promote a healthy work/life balance across the organisation. We offer an appealing working prospect for our people. With numerous wellbeing initiatives, shared parental leave, study assistance and sabbaticals, we will help you meet your immediate responsibilities and your long-term goals.

Working flexible hours - flexing the times when you work in the day to help you fit everything in and work when you are the most productive

Working for you

We know that your well-being and happiness are key to a long and successful career. These are some of the benefits we are delighted to offer:

Dutch Share Purchase PlanAnnual Profit Share BonusComprehensive Pension PlanHome, office or commuting allowanceGenerous vacation entitlement and option for sabbatical leaveMaternity, Paternity, Adoption and Family Care leaveFlexible working hoursPersonal Choice budgetVariety of online training courses and career roadshowsWellbeing programs and gym facility in the officeInternal communities and networksVarious employee discountsRecruitment introduction rewardWork from anywhereEmployee Assistance Program (global)Annual Event

About Data Science at Elsevier

Elsevier is one of the world’s leading publishers of trusted scientific, technology, and medical content. Building on that foundation of content, we leverage data science and AI to deliver knowledge and analytics products that advance science and improve healthcare outcomes. Therefore, an efficient, streamlined, and optimized data science development process is key to sustaining innovation and business growth, especially with the opportunities ahead with GenAI. Elsevier is committed to adhere to our RELX Responsible AI Principles, for the development and deployment of all of our AI solutions. 
 

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