Service Development Manager – AI Data Structuring & Readiness

Product Dev Sppt Analyst III

Do you like working with data and analytics to gain insight to solve problems?

Do you enjoy collaborating across teams to build and deliver products that make a difference?

Platform Operations (Platform Ops) is a fast-growing team within Data Operations, focused on powering the next-generation Research Data Platform built on data mesh principles. Our team enables scalable, high-quality data services that support key Elsevier products such as Scopus, Leap Space, Sci Val, Reaxys, and other leading research solutions used globally. We operate at the intersection of data engineering, platform services, and supplier ecosystem management, ensuring that data products are reliable, governed, and continuously improving.

Data Modeling is a senior technical leader within the Data Operations function, responsible for defining and advancing structured data models, semantic frameworks, and scalable AI-enabled processing workflows. This role sets technical standards for data modeling, Knowledge Graph development, and LLM operationalization across Data Operations. The position ensures that complex business, product, and operational requirements are translated into governed, production-ready data structures and interoperable processing pipelines.

Data Modeling & Structured Content Leadership

• Define and govern logical data modeling standards across Data Operations.
• Design and maintain scalable data models supporting high-volume data processing and enrichment workflows.
• Establish canonical data principles to ensure consistency, interoperability, and governance alignment.
• Define normalization standards, transformation logic, and metadata structures for structured content ecosystems.
• Drive adoption of reusable, extensible, and future-ready modeling frameworks.

Knowledge Graph & Semantic Framework Strategy

• Lead the design and evolution of semantic data models supporting Knowledge Graph initiatives.
• Define entity-relationship frameworks, ontology-aligned structures, and semantic linking strategies.
• Apply Linked Data and RDF principles to enhance contextual data relationships and interoperability.
• Provide technical leadership in integrating Knowledge Graph models within operational data workflows.
• Guide semantic enrichment strategies to improve discoverability, entity resolution, and downstream AI applications.

Technical Specification & Design Governance

• Lead comprehensive technical specification writing for complex data processing, enrichment, transformation, and semantic modeling initiatives.
• Translate business and product requirements into structured data definitions, schema designs (XSD, JSON Schema), mapping rules, and validation frameworks.
• Establish traceability between business requirements, technical specifications, and operational implementation.
• Define documentation standards and best practices for data modeling and workflow design.

Content Processing & Workflow Excellence

• Architect and optimize end-to‑end data and content processing workflows, including ingestion, enrichment, semantic tagging, validation, transformation, and structured output delivery.
• Define validation checkpoints, quality control mechanisms, and risk mitigation controls within operational pipelines.
• Improve operational throughput, automation maturity, and scalability.
• Establish structured testing strategies (unit, integration, regression) for complex transformations.
• Standardize workflow frameworks to enhance operational resilience and performance consistency.

Strategic Collaboration & Advisory Role

• Partner with Product, Engineering, and Operations leadership to align structured data and semantic frameworks with long-term strategic objectives.
• Conduct impact assessments for new data models, workflow enhancements, enrichment initiatives, and system integrations.
• Act as the senior technical advisor for complex data, Knowledge Graph, and AI enablement initiatives.
• Influence roadmap decisions related to structured data, semantic intelligence, and automation strategy.

• Bachelor’s or Master’s degree in Computer Science, Information Systems, Data Engineering, or…