At a Glance
- Tasks: Lead analytics for search systems, define metrics, and generate insights to enhance user experience.
- Company: Join Elsevier, a global leader in information and analytics for science and healthcare.
- Benefits: Enjoy flexible hours, health benefits, and a supportive work/life balance.
- Other info: Opportunities for career growth and involvement in innovative AI projects.
- Why this job: Make a real impact on healthcare and research through data-driven insights.
- Qualifications: Experience in data analysis, SQL, Python, and data visualisation tools required.
The predicted salary is between 60750 - 74250 £ per year.
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 LeapSpace to ClinicalKey AI, PharmaPendium, 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., 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.
Data Visualization & Communication
- 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.
Data Management & Tooling
- Ensure high standards for data quality, metric consistency, and instrumentation reliability.
- 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.
Qualifications:
- 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.
- Proven ability to translate complex data into actionable insights and influence decisions.
- Exposure to clickstream data, user behavior analytics, and event tracking systems.
- Experience supporting evaluation of ML-based ranking or retrieval systems.
We promote a healthy work/life balance across the organization. With numerous wellbeing initiatives, shared parental leave, study assistance and sabbaticals, we will help you meet your immediate responsibilities and your long-term goals.
- Flexible working hours - flexing the times when you work in the day to help you fit everything in and work when you are the most productive.
- Holiday allowance with the option to buy additional days.
- Health screening, eye care vouchers and private medical benefits.
- Life assurance, plus optional additional life cover and spouse's life cover at own cost.
- Access to a competitive contributory pension scheme.
- Save As You Earn share option scheme.
- Access to optional self funded benefits, including electric vehicle scheme, cycle to work scheme, dental insurance, critical illness cover, health cash plan, personal travel insurance.
- Travel season ticket loan.
- Paid time off when you become a parent, and paid time off for carers.
- Access to emergency care for both the elderly and children.
As a global leader in information and analytics, we help researchers and healthcare professionals advance science and improve health outcomes for the benefit of society. Building on our publishing heritage, we combine quality information and vast data sets with analytics to support visionary science and research, health education, and interactive learning, as well as exceptional healthcare and clinical practice.
Data Analyst - Data Analityk in London employer: Elsevier
At Elsevier, we pride ourselves on being an excellent employer, particularly for our Java Software Engineer role in Oxford. Our vibrant work culture fosters collaboration and innovation, while our commitment to employee growth is evident through continuous learning opportunities and flexible working arrangements that promote a healthy work-life balance. Join us to be part of a team that values your contributions and supports your professional journey in the exciting field of scientific knowledge sharing.