Jobs at RELX

Own AI-powered product capabilities from discovery through launch and adoption. Translate customer and business needs into requirements, prioritize backlogs, write user stories, define acceptance criteria, and collaborate with Engineering, Data Science, UX, and business teams. Support customer discovery, experimentation, testing, demonstrations, and continuous improvement while tracking product success metrics and promoting transparency, privacy, reliability, fairness, security, explainability, and customer trust.

Own complex analytics projects from business questions through delivery, developing reliable data products and solutions. Partner with product managers, analytics engineers, technologists, and senior stakeholders to shape data-driven strategy. Apply data preparation, blending, governance, and emerging AI techniques while coaching junior colleagues in analysis design, stakeholder engagement, and project management.

Leads multiple distributed engineering teams supporting SciVal’s large-scale research analytics platform. Sets technical strategy, architectural standards, and roadmap execution across frontend, backend, data, and quality engineering. Develops engineering leaders, manages workforce planning, and drives platform modernization, reliability, security, and operational resilience. Partners with Product, Data, Architecture, UX, customers, and commercial stakeholders to deliver analytics, AI-assisted, search, and agent-ready capabilities.

Supports the Senior Product Manager in shaping and delivering enhancements for SSRN, Elsevier’s preprint server. Responsibilities include writing user stories and acceptance criteria, gathering requirements, managing the product backlog, supporting Agile sprint ceremonies, tracking releases in JIRA and Aha, prioritizing defects, producing analytics reports, and assisting with discovery, launch readiness, and stakeholder communications.

Lead and expand relationships with a small number of high-value insurance clients, drive retention and revenue through strategic account plans, cross-sell/upsell, forecasting, and C-suite engagement. Coordinate internal teams, inform product roadmap with client insights, ensure service delivery, and represent the company at industry events. Requires frequent travel.

Lead customer-facing data science and AI projects for commodity markets: identify high-impact opportunities, prototype and deploy ML/AI solutions (including LLMs and agentic approaches), measure business impact, collaborate with product, engineering and domain experts, and share learnings to shape ICIS data and AI products.

Own a product or significant area within Interfolio’s Faculty Information System. Develop product strategy and roadmaps, conduct customer discovery, prioritize opportunities, build business cases, identify AI opportunities, and guide products from concept through launch and ongoing improvement. Collaborate with faculty, researchers, institutional users, engineering, design, marketing, sales, customer success, and support while applying technical fluency across SaaS products, APIs, integrations, data, and architecture.

Designs, develops, tests, and supports reliable data engineering solutions for insurance data products. Responsibilities include data transfers, profiling, validation, quality management, issue resolution, data modeling, workflow management, code reviews, troubleshooting, and automation. The role collaborates with technical teams and business stakeholders to translate requirements into scalable, maintainable solutions while exploring AI-assisted engineering practices.

Leads regional solution sales across Northern Europe, driving new business, renewals, upselling, and cross-selling. Manages, coaches, and develops Solution Account Managers while overseeing forecasting, pipeline performance, account planning, and complex negotiations. Builds senior customer relationships and collaborates with Customer Success, Product, Marketing, Finance, Pricing, and Sales leadership in an international matrixed organization.

Own the strategy, roadmap, development lifecycle, and go-to-market activities for fraud analytics products. Lead customer discovery, prioritize product improvements, analyze complex data, collaborate with development and data science teams, and use market and customer insights to improve user outcomes. The role requires fraud prevention expertise, statistical modeling and AI/machine learning knowledge, strong stakeholder communication, and flexible UK-US working hours.

Leads business development for the UK Personal Lines Insurance Claims market, exceeding revenue targets, identifying new opportunities, and shaping sales strategy. Serves as a Claims subject matter expert, supports client engagements, builds senior stakeholder relationships, contributes market insight to product development, and represents the company at industry events. Provides leadership to a growing Claims sales team while collaborating cross-functionally with account management, product, implementation, and sales support teams.

Build and deploy end-to-end data science and AI solutions, including scalable data pipelines, machine learning and generative AI workflows. Translate product and business questions into measurable analytics use cases, analyze product data, establish evaluation and monitoring practices, and collaborate with product, engineering, and analytics teams to deliver business impact.

Writes and updates inheritance tax content, including research materials and practical guidance. Reviews AI-powered tax workflows for technical accuracy and practitioner relevance, collaborates on commissioned content, and contributes to the strategic direction of Tolley’s tax offering. The role requires expertise in inheritance tax, trusts, estates, and personal tax, strong writing and communication skills, and the ability to use AI tools critically in tax research and content creation.

Designs, builds, and operates reliable cloud infrastructure across AWS and Azure. Responsibilities include developing Terraform infrastructure as code, managing EKS and AKS Kubernetes clusters, maintaining CI/CD pipelines, improving security and cost efficiency, troubleshooting distributed infrastructure issues, implementing monitoring and alerting, and collaborating with engineering and architecture teams on platform standards and documentation.

Leads UK and Ireland strategy for Customer Data Management, using customer, market, regulatory, competitive and commercial insights to define priorities. Shapes propositions, positioning, packaging and business cases; translates customer needs into product, data, technology and operational requirements; leads cross-functional initiatives; measures customer value; and supports Sales, Pre-Sales and Marketing with value propositions and market narratives.

Lead the architecture and evolution of a Snowflake-based operational data platform. Design secure, governed, scalable data warehouse solutions, real-time ingestion, API integrations, AI-enabled capabilities, and natural-language querying interfaces. Define data flows, schemas, roadmaps, architectural standards, and governance while collaborating with engineering, data, business, and executive stakeholders. Troubleshoot complex platform issues, guide technical direction, and promote modern data engineering practices across enterprise systems.

Develop and align global go-to-market strategies across customer personas and enterprise offerings. The role translates customer and market insights into priorities, commercialization plans, governance, operating rhythms, and measurable growth initiatives. It partners with senior GTM leaders, leads planning for product launches and portfolio changes, identifies cross-persona opportunities and dependencies, and monitors performance through shared metrics and customer feedback. Success requires strong strategic, analytical, financial, facilitation, and stakeholder-influencing skills in complex, matrixed organizations.

Partner with finance and operations to analyze performance, build and maintain budgeting/forecast models, validate and troubleshoot messy data, produce dashboards and variance/root-cause analyses, and deliver actionable insights to improve commercial outcomes.

Lead a global Learning & Performance team to design and deliver a sales and customer success curriculum, embed Challenger methodology, build assessments and certifications, align learning with commercial strategy, use data to measure impact, and partner cross-functionally to drive sustained behaviour change and performance.

Lead identification, development, and global deployment of AI and automation solutions to optimize forms and precedents content operations. Prioritize opportunities, collaborate with cross-functional teams, ensure governance and quality, integrate solutions, report outcomes to leadership, and drive continuous improvement and responsible AI practices.