Senior Data Scientist I

Overview

As a Senior Data Scientist at Elsevier Life Sciences Data Science, you will design, build, and productionize GenAI, NLP, and RAG solutions to enrich life sciences products. You will own end-to-end data science life cycles, delivering production-grade Python and collaborating with engineers and domain experts. You’ll optimize RAG pipelines, manage multilingual data, and develop agentic AI components with an emphasis on reliability and impact. This role offers the chance to shape cutting-edge analytics for Reaxys, Embase, and Pharmapendium, contributing to science and health outcomes.

Pay / Benefits

• flexible working hours
• wellbeing initiatives
• shared parental leave
• study assistance
• sabbaticals
• country-specific benefits

Responsibilities

• Data collection, analysis, and model development with quality metrics
• Create production-ready Python packages and deploy with software engineering
• Optimize retrieval augmented generation (RAG) pipelines for content ingestion, translation, and contextual retrieval
• Ingest, preprocess, and transform large multilingual datasets
• Build AI agentic models integrated with RAG pipelines
• Rigorous testing and evaluation of AI models for performance and reliability
• End-to-end quality assessments and monitoring for pipeline robustness
• Collaborate with cross-functional teams to integrate AI into products
• Lead and manage small projects and mentor junior data scientists
• Stay updated on AI/ML/NLP advancements

Key requirements

• 5+ years of applied experience in data science with Generative AI, NLP, and ML
• Proficiency in Python for analysis, modeling, and deployment
• Strong experience with transformer models
• Experience with Generative AI tech including LLMs via API, evaluation tools, and prompt engineering
• Knowledge of RAG pipelines and practical implementation
• Experience building Agentic RAG systems
• Experience with LangChain or similar AI agent management frameworks
• Knowledge of deep learning, reinforcement learning, transfer learning
• Familiarity with cloud platforms (Bedrock, AWS, Azure) for production pipelines
• Proficiency in data visualization, version control (GitLab/GitHub), Jira, Agile
• Proficient in OpenSearch and Databricks
• Strong problem-solving and collaboration skills

• strong communication
• team-oriented
• mentoring
• NLP
• GenAI
• transformer models

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