**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 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.
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. Familiarity 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.
Experience Building Agentic RAG Systems Is Strong Requirements. Familiarity in LangChain, AutoGen, Haystack, MCP or similar AI agent management tools.
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.
5+ years of relevant applied experience in data science, with a focus on Generative AI, NLP, and machine learning.
Proficiency in Python for advanced 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 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 flexible work environment that meets the needs of a diverse team. Whether you prefer remote work, hybrid work, or on-site collaboration, we want to support your success. Our well-being initiatives include shared parental leave, study assistance, sabbaticals, and access to wellness programs.
Working For you: We aim to support you in all areas of life. Our comprehensive benefits package includes:
About Us:
Our organization is a global leader in information and analytics, aiding researchers and healthcare professionals in advancing science and improving health outcomes for society. We combine quality information and vast data sets with analytics to support visionary science, research, health education, interactive learning, and exceptional healthcare and clinical practice. At Elsevier, your work contributes to addressing the world's grand challenges and fostering a more sustainable future. We harness innovative technologies to support science and healthcare, partnering for a better world.
We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location.
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