Elsevier is looking for a Senior Data Scientist I to join our Data Science Health team. You will be pivotal in developing and deploying Generative AI models and solutions, engaging in the full project lifecycle from design to ongoing enhancement.
What You'll Do
- Design, develop, and deploy Generative AI, RAG, and Agentic AI solutions to meet business needs.
- Collect data, perform analysis, develop models, and conduct quality assessments, presenting findings to stakeholders.
- Create production-ready Python packages for data science pipelines and coordinate deployment with technology teams.
- Optimize and customize Retrieval Augmented Generation (RAG) pipelines and build Agentic RAG systems.
- Fine-tune large language models (LLMs) and transformer models to enhance accuracy.
- Implement guardrails and evaluation mechanisms to ensure responsible and ethical AI usage.
- Conduct rigorous testing and evaluation of AI models to ensure performance and reliability.
- Maintain data science pipelines against model drift and develop automatic re-training strategies.
- Work collaboratively with cross-functional teams to integrate AI solutions into products.
- Mentor junior data scientists and contribute to team knowledge-sharing.
- Stay current with advancements in AI, machine learning, and NLP technologies.
What We're Looking For
- A Master’s or Ph.D. in Computer Science, Data Science, Artificial Intelligence, or a related field.
- 7+ years of applied experience in data science, focusing 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 LLMs.
- Proficiency in Generative AI technologies, including LLM API access, evaluation tools, and prompt engineering.
- Knowledge of various RAG pipelines and their practical implementation.
- Experience with deep learning, neural networks, reinforcement learning, and transfer learning.
- Familiarity with traditional machine learning algorithms for model building and validation.
- Understanding of AI ethics, guardrail implementation, and evaluation metrics.
- Familiarity with cloud platforms like AWS, Azure, or Bedrock for deployment.
- Proficiency in data visualization tools and techniques.
- Experience with GitLab or GitHub, Jira, and working in an Agile environment.
- Proficient in using *nix systems, open-source software, Jupyter Notebook, and cloud computing.
- Excellent problem-solving, analytical skills, and strong attention to detail.
- Strong communication and teamwork abilities.
Nice to Have
- Experience with end-to-end model deployment, including leveraging AI agents, Model Context Protocol (MCP), and cloud platforms like AWS Bedrock or Azure.
- Experience in Java is considered an asset.
Technical Stack
- Python, Generative AI, Machine Learning, Natural Language Processing (NLP), Transformer models
- Large Language Models (LLMs), Retrieval Augmented Generation (RAG), Agentic AI
- LangChain, AutoGen, Haystack, Model Context Protocol (MCP)
- AWS, AWS Bedrock, Azure, GitLab, GitHub, Jira, Jupyter Notebook
Team & Environment
You will be joining the Data Science Health team.
Benefits & Compensation
- Health insurance for you and your family.
- Enhanced health insurance options at competitive rates.
- Group life insurance and group accident insurance.
- Flexible working arrangements for work-life balance.
- Employee assistance programs for personal and work-related support.
- Medical screenings and modern family benefits (maternity, paternity, adoption support).
- Long-service awards and new baby gifts.
- Subsidized meals at specific locations.
- Various paid time-off options, including casual, sick, privilege, compassionate, and special sick leave.
- Free transportation for home-office-home travel in select locations.
- Healthy work/life balance, 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.
