Senior Data Analyst I

About the Role Senior Data Analyst I to lead analytics and evaluation for Elsevier’s search and retrieval systems. Own analytical workflows, define measurement strategies, and generate insights that directly improve ranking quality, relevance, and user experience. This role requires deep experience in search analytics, experimentation, and data visualization, with the ability to work autonomously and influence cross-functional decisions.

What You'll Do

• Lead analysis of search and retrieval system performance, including ranking quality and relevance; define standard metrics (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.
• Design and lead A/B testing and experimentation frameworks for search and ranking improvements; define success metrics and experiment strategies; ensure statistical rigor.
• Build reusable experimentation templates and scalable analysis workflows.
• Own and evolve dashboards and reporting; enable self-service analytics for partners through well-designed tools; communicate insights with clear data storytelling.
• Collaborate with engineering to improve logging, tracking, and observability of search systems.

What We're Looking For

• Master’s or PhD in Data Analytics, Statistics, Computer Science, or 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 (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).
• Proven ability to translate complex data into actionable insights and influence decisions.

Nice to Have

• PhD in Data Analytics, Statistics, Computer Science, or related field (or equivalent practical experience).
• Experience working on search, ranking, or recommendation systems.
• Familiarity with information retrieval concepts (indexing, ranking, query understanding).
• Exposure to clickstream data, user behavior analytics, and event tracking systems.
• Experience supporting evaluation of ML-based ranking or retrieval systems.
• Familiarity with RAG systems or GenAI applications.

Compensation & Benefits

• Holiday allowance with option to buy additional days; Health screening, eye care vouchers, and private medical benefits; Life assurance and optional life cover at cost; Spouse’s life cover option.
• Competitive contributory pension scheme; Save As You Earn share option scheme.
• Flexible/modern benefits and wellbeing initiatives; study assistance and sabbaticals where applicable.