Jobs at Elsevier

Partners with senior leaders across Operations and Global Functions to drive budgeting, forecasting, performance analysis, cost management, scenario planning, and financial decision support. Translates operational and financial data into actionable insights, models transformation and AI-enabled workflow impacts, improves cost transparency and productivity, and ensures strong financial governance, reporting accuracy, and accountability.

Leads digital marketing for scientific journals and conferences, including email campaigns, website and webpage management, marketing technology administration, analytics, conversion optimization, technical project planning, and workflow improvement. The role supports marketing SLAs, resolves technical issues, evaluates emerging technologies, advises stakeholders on online marketing best practices, and coaches non-technical colleagues.

Designs and implements methods for linking and aligning taxonomies and ontologies. Models controlled vocabularies using SKOS, SKOS-XL, and OWL; queries semantic data with SPARQL; integrates data through REST APIs; and develops Python tools for modeling and integration workflows. Collaborates with stakeholders to translate data needs into semantic models and may mentor engineers. Preferred experience includes large-scale taxonomy alignment, AWS, Git, CI/CD, SHACL, and life sciences.

Leads the technical design, development, and evolution of enterprise sales and marketing data platforms. Builds scalable Snowflake and dbt pipelines, defines data models and reliability standards, drives CI/CD and DevSecOps practices, mentors engineers, partners with stakeholders, and leads complex initiatives from discovery through production. The role also conducts incident analysis, reduces technical debt, and evaluates AI-assisted engineering technologies.

Administer and optimize the Docebo learning management platform supporting global sales teams. Responsibilities include technical support, configuration, troubleshooting, integrations, automation, identity provisioning, SSO, API data flows, security governance, rollouts, testing, documentation, and continuous improvement. The role partners with business administrators, technology teams, and product support to maintain platform reliability and expand adoption.

The Quality Test Engineer II creates and executes manual regression, functional, and end-to-end tests for Salesforce-based software products. The role supports sprint delivery, collaborates with technical and non-technical teams, participates in Agile ceremonies, and applies quality engineering practices across the SDLC and STLC. The position emphasizes manual testing while encouraging development of automation testing skills.

Develop and govern enterprise Salesforce solutions across Service Cloud and Experience Cloud, including Apex, LWC, integrations, data models, Flow automation, and AI agents. Translate stakeholder needs into scalable designs, resolve complex technical issues, conduct testing and code reviews, support compliant release processes, and mentor junior engineers. The role also evaluates AI-generated code for security and quality, maintains platform expertise, and collaborates across Salesforce and adjacent sales technology platforms.

Analyzes and improves Salesforce Service Cloud and Experience Cloud processes, gathers requirements, creates user stories and acceptance criteria, and supports Agile delivery. The role evaluates AI and automation opportunities using Agentforce, Einstein, chatbots, and generative AI. It also performs Salesforce development and testing with Apex and Lightning Web Components, facilitates workshops, advises stakeholders, and supports responsible AI adoption through data, process, and change-impact assessments.

Develops and maintains Salesforce solutions across Service Cloud, Experience Cloud, and AI-powered service workflows. Responsibilities include Apex and LWC development, integrations, data modeling, automation, testing, code reviews, release governance, bug resolution, and technical collaboration with business and delivery teams. The role also builds self-service portals, supports case management capabilities, evaluates Agentforce and Einstein features, and participates in escalation or on-call rotations.

Develop and support complex Salesforce solutions across Apex, Lightning Web Components, Flow, integrations, data models, and AI-driven Agentforce automations. Translate business requirements into scalable architectures, resolve technical issues, enforce development and compliance standards, and collaborate with cross-functional teams. The role also involves mentoring junior engineers, reviewing AI-generated code, designing tests, managing releases, and staying current with Salesforce and AI platform developments.

Designs, develops, and supports complex enterprise Salesforce solutions across Apex, LWC, Flow, integrations, and large-scale data models. The role translates business requirements into scalable architecture, resolves technical issues, governs releases, and develops AI-driven agents and automations using Agentforce and related tooling. It also requires code reviews, testing, compliance alignment, stakeholder collaboration, and mentoring junior engineers.

Own end-to-end UX design for Salesforce-based enterprise platforms supporting academic editors. Responsibilities include user research, workflow analysis, information architecture, wireframing, prototyping, user testing, high-fidelity UI design, design-system contribution, accessibility compliance, and post-launch feedback measurement. Collaborate with product, engineering, and global editorial stakeholders to create and iteratively improve complex, data-rich workflows.

Owns quality strategy and test engineering for Salesforce-based deterministic and AI-driven systems. Designs automated functional, regression, integration, performance, and AI evaluation testing; develops golden datasets, rubrics, and regression benchmarks; investigates defects, hallucinations, bias, drift, and inconsistent outputs; supports compliance evidence and production monitoring; and mentors junior QA engineers. Collaborates with developers, analysts, product owners, and administrators to establish testable requirements and responsible-AI standards.

Develop and support Salesforce CRM solutions for global editorial, licensing, sales, and marketing teams. Responsibilities include end-user support, business analysis, requirements gathering, integrations, troubleshooting, documentation, UAT support, process improvement, solution reviews, and Salesforce development. The role serves as a business-facing Salesforce subject matter expert and works with stakeholders to maintain a stable, scalable, and reliable Salesforce deployment.

Independently perform complex analytics and large-scale data preparation using Databricks, Snowflake, SQL, Python and Spark. Collaborate with Product Owners and Data Scientists to validate data products, evaluate model precision/recall, produce insights and recommendations, and communicate findings to stakeholders. Ensure data quality and support product improvements.

Runs multilingual AI quality evaluations across translation tools and models, manages reviewer networks, and maintains terminology assets such as term bases and style guides. Presents quality findings and recommendations to product and localization teams, supports stakeholders on evaluation and terminology processes, and collaborates with AI, data science, platform, and content teams in a global matrixed environment.

Develop and execute automated functional and non-functional tests using JavaScript, TypeScript, Playwright, and Selenium. Build scalable test frameworks, perform primarily end-to-end and API testing, ensure appropriate feature coverage, and investigate production incidents. Collaborate with agile teams to support consistent, on-time delivery of high-quality software.

Leads a team of scientific data analysts supporting Reaxys, Embase, and future AI-enabled life sciences platforms. Oversees search and API quality evaluation, data discoverability, testing, feature releases, customer-focused insights, and quality standards. Uses scientific expertise, data analysis, scripting, databases, cloud platforms, and AI-enabled testing workflows to improve platform reliability and relevance. Coordinates stakeholders, advances projects, documents work, and presents recommendations for product and data improvements.

Owns the full sales cycle for complex, high-value AI research workspace opportunities, from prospecting and discovery through negotiation and closure. Builds executive stakeholder relationships, generates new business, supports strategic renewals, leads workshops, develops business cases, and communicates measurable value from AI-powered research and knowledge workflow solutions. Requires enterprise sales expertise, AI fluency, consultative selling skills, and extensive regional travel.