Senior Data Analyst

About The Team

Elsevier’s mission is to help researchers, clinicians, and life sciences professionals advance discovery and improve health outcomes through trusted content, data, and analytics. As the landscape of science and healthcare evolves, we are pioneering intelligent discovery experiences — from Scopus AI and Leap Space to Clinical Key AI, Pharma Pendium, and next-generation life sciences platforms. These products leverage retrieval-augmented generation (RAG), semantic search, and generative AI to make knowledge more discoverable, connected, and actionable across disciplines.

The Search & AI Evaluation team sits within the Platform Data Science organization and is responsible for advancing enterprise-scale search, retrieval, and evaluation capabilities across Elsevier's global products.

We are looking for a Senior Data Analyst to lead analytics and evaluation efforts for search and retrieval systems. You will own key analytical workflows, define measurement strategies, and generate insights that directly improve ranking quality, relevance, and user experience. This role is ideal for someone with deep experience in search analytics, experimentation, and data visualization, who can operate with high autonomy and influence decision-making across cross-functional teams.

• Perform a leading role in analysis of search and retrieval system performance, including ranking quality and relevance.
• Help define and standardize search evaluation metrics (e.g., NDCG, MAP, recall, precision, CTR).
• Analyze query behavior, user interaction signals, and content performance to identify optimization opportunities.
• Conduct deep-dive analyses on ranking performance, query intent, and retrieval gaps.
• Support evaluation of downstream applications (including GenAI-powered features) where they depend on retrieval quality.

• Help design and lead A/B testing and experimentation frameworks for search and ranking improvements.
• Partner with product and data science to define success metrics and experiment strategies.
• Ensure statistical rigor in experiment design, analysis, and interpretation.
• Build reusable experimentation templates and scalable analysis workflows.

• Own and evolve dashboards and reporting systems tracking search performance and user engagement.
• Develop clear, actionable data storytelling to communicate insights to technical and business stakeholders.
• Enable self-service analytics for partners through well-designed reporting tools.

• Work with large-scale datasets using modern platforms (e.g., Databricks, Spark, SQL-based systems).
• Ensure high standards for data quality, metric consistency, and instrumentation reliability.
• Collaborate with engineering to improve logging, tracking, and observability of search systems.

• Act as a key analytics partner to search data scientists, engineers, and product teams.
• Help elevate the team’s understanding of retrieval performance and measurement frameworks.

• Master’s or PhD in Data Analytics, Statistics, Computer Science, or a related field (or equivalent practical experience)
• Significant experience in data analysis, business intelligence, or analytics roles
• Proficiency in SQL and Python for large-scale data analysis
• Advanced experience with data visualization and BI tools (e.g., Tableau, Power BI, Looker, matplotlib, seaborn)
• Experience working with Databricks or similar large-scale data platforms
• Excellent understanding of experimentation design, A/B testing, and statistical analysis
• Experience defining and analyzing search/retrieval metrics (e.g., NDCG, recall, precision, ranking metrics)
• Proven ability to translate complex data into actionable insights and influence decisions

• PhD in Data Analytics, Statistics, Computer Science, or a related field (or equivalent practical experience)
• Experience working on search, ranking, or recommendation systems
• Familiarity with information retrieval concepts (e.g., indexing, ranking, query understanding)
• Exposure to clickstream…