Elsevier is hiring a Senior Data Scientist II to play a pivotal role in developing and deploying cutting-edge Generative AI models for the health sciences domain. You will be responsible for the entire lifecycle of data science projects, ensuring ethical and responsible use of AI.
What You'll Do
- Collect data, perform analysis, develop models, define quality metrics, and present to stakeholders.
- Create production-ready Python packages for each component of data science pipelines and coordinate their deployment.
- Design, develop, and deploy Generative AI models and solutions that meet specific business needs.
- Optimize and customize Retrieval Augmented Generation (RAG) pipelines.
- Perform large-scale data ingestion, preprocessing, and transformation of multilingual content.
- Build Agentic RAG systems.
- Fine-tune large language models (LLMs) and transformer models to enhance accuracy and relevance.
- Implement guardrails and evaluation mechanisms for responsible and ethical AI usage.
- Conduct rigorous testing and evaluation of AI models for high performance and reliability.
- Integrate data science components and ensure end-to-end quality assessment.
- Maintain the robustness of pipelines against model drift and ensure consistent output quality.
- Establish reporting processes for pipeline performance and develop automatic re-training strategies.
- Work collaboratively with cross-functional teams to integrate AI solutions into existing products.
- Mentor junior data scientists and contribute to the team's knowledge-sharing culture.
- Stay up-to-date with the latest advancements in AI, machine learning, and NLP.
What We're Looking For
- 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, 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 ML algorithms such as random forests, SVM, logistic regression, and Bayesian modelling.
- Understanding of AI ethics, guardrail implementation, and evaluation metrics.
- Familiarity with cloud platforms (e.g., Bedrock, AWS, Azure) for model deployment and 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 and teamwork skills.
Nice to Have
- Experience building Agentic RAG systems.
- Experience in LangChain, AutoGen, Haystack, MCP or similar AI agent management tools.
- Experience with end-to-end model deployment, including leveraging AI agents, Model Context Protocol (MCP), and cloud platforms like AWS (including AWS Bedrock) or Azure.
- Experience in Java considered an asset.
Technical Stack
- Python, Generative AI, Large Language Models (LLMs), Retrieval Augmented Generation (RAG), Agentic AI, Natural Language Processing (NLP), Transformer models
- LangChain, AutoGen, Haystack, Model Context Protocol (MCP)
- AWS, AWS Bedrock, Azure
- GitLab, GitHub, Jira
- *nix systems, Jupyter Notebook
Team & Environment
You will be part of the Data Science Health team at Elsevier.
Benefits & Compensation
- Health insurance for you and your family.
- Enhanced health insurance options at competitive rates.
- Group life insurance for financial security.
- Group accident insurance for protection against accidental death and permanent disability.
- Flexible working arrangements for work-life balance.
- Employee assistance programs for personal and work-related support.
- Medical screenings prioritize your well-being.
- Modern family benefits, including maternity, paternity, and adoption support.
- Long-service awards to recognize dedication.
- New baby gifts to celebrate parenthood.
- Subsidized meals at specific locations.
- Various paid time-off options, including casual leave, sick leave, privilege leave, compassionate leave, special sick leave, and public holidays.
- Free transportation for home-office-home travel in select locations.
- Healthy work/life balance with well-being initiatives, shared parental leave, study assistance, and sabbaticals.
We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law.
