About this role
Salary: £65,000 - 105,000 per year
Requirements: Masters or PhD in Data Analytics, Statistics, Computer Science, or a related field, or equivalent practical experienceSignificant experience in data analysis, business intelligence, or analytics rolesProficiency in SQL and Python for large-scale data analysisAdvanced experience with data visualization and BI tools such as Tableau, Power BI, Looker, matplotlib, or seabornExperience working with Databricks or similar large-scale data platformsExcellent understanding of experimentation design, A/B testing, and statistical analysisExperience defining and analyzing search and retrieval metrics such as NDCG, recall, precision, and ranking metricsProven ability to translate complex data into actionable insights and influence decisionsPhD in Data Analytics, Statistics, Computer Science, or a related field, or equivalent practical experienceExperience working on search, ranking, or recommendation systemsFamiliarity with information retrieval concepts such as indexing, ranking, and query understandingExposure to clickstream data, user behavior analytics, and event tracking systemsExperience supporting evaluation of ML-based ranking or retrieval systemsFamiliarity with RAG systems or GenAI applications Responsibilities: Lead analysis of search and retrieval system performance, including ranking quality and relevanceHelp define and standardize search evaluation metrics such as NDCG, MAP, recall, precision, and CTRAnalyze query behavior, user interaction signals, and content performance to identify optimization opportunitiesConduct deep-dive analyses on ranking performance, query intent, and retrieval gapsSupport evaluation of downstream applications, including GenAI-powered features, where they depend on retrieval qualityHelp design and lead A/B testing and experimentation frameworks for search and ranking improvementsPartner with product and data science to define success metrics and experiment strategiesEnsure statistical rigor in experiment design, analysis, and interpretationBuild reusable experimentation templates and scalable analysis workflowsOwn and evolve dashboards and reporting systems tracking search performance and user engagementDevelop clear, actionable data storytelling to communicate insights to technical and business stakeholdersEnable self-service analytics for partners through well-designed reporting toolsWork with large-scale datasets using modern platforms such as Databricks, Spark, and SQL-based systemsEnsure high standards for data quality, metric consistency, and instrumentation reliabilityCollaborate with engineering to improve logging, tracking, and observability of search systemsAct as a key analytics partner to search data scientists, engineers, and product teamsHelp elevate the teams understanding of retrieval performance and measurement frameworks Technologies: AIBusiness IntelligenceDatabricksSupportLookerPower BIPythonRAGSQLSparkTableau More:
We are Elsevier, a global leader in information and analytics, helping researchers, clinicians, and life sciences professionals advance discovery and improve health outcomes through trusted content, data, and analytics. Our Search & AI Evaluation team sits within the Platform Data Science organization and advances enterprise-scale search, retrieval, and evaluation capabilities across our global products, including Scopus AI, LeapSpace, ClinicalKey AI, PharmaPendium, and next-generation life sciences platforms. We offer a culture of innovation, collaboration, and excellence, with flexible working hours, healthy work/life balance, wellbeing initiatives, shared parental leave, study assistance, sabbaticals, and a wide range of country-specific benefits. Our location for this role is London Wall, and we are committed to providing a fair and accessible hiring process.
last updated 40 week of 2026