Full-Time

Service Development Manager

AI Data Structuring & Readiness

Updated on 8/25/2026

RELX

RELX

1,001-5,000 employees

Global information analytics and decision tools

No salary listed

Gurugram, Haryana, India + 2 more

More locations: Chennai, Tamil Nadu, India | Bengaluru, Karnataka, India

In Person

Bachelor's, Master's

Category
Data & Analytics (1)
Required Skills
LLM
Software Testing
SQL
Data Engineering
RAG
Data Modeling
Data Analysis
HTML/CSS

Get referred to RELX

See people who can refer or advise you

Requirements
  • A Bachelor's or Master's degree in Computer Science, Information Systems, Data Engineering, or a related field.
  • 8–12+ years of experience in data modeling, structured data processing, semantic modeling, or large-scale data operations environments.
  • Strong expertise in content processing, enrichment workflows, metadata management, or structured data ecosystems.
  • Demonstrated experience leading Knowledge Graph and semantic data modeling initiatives.
  • Proven excellence in technical specification writing and workflow design governance.
  • Advanced SQL and relational data design.
  • XML schema design using XSD.
  • JSON schema development and transformation logic.
  • XML/HTML5 structured content modeling.
  • Linked Data and RDF principles.
  • Knowledge Graph concepts, ontology modeling, and semantic data structures.
  • Data normalization, taxonomy design, and metadata governance.
  • Strong understanding of structured content processing techniques.
  • End-to-end workflow architecture and process optimization.
  • Data validation, transformation, and quality governance frameworks.
  • API integration and interoperability patterns.
  • Data modeling and documentation tools.
  • Strong understanding of GenAI and large language model technologies.
  • Experience integrating large-language-model-driven capabilities within structured operational workflows.
  • Familiarity with Retrieval-Augmented Generation concepts.
  • Awareness of vector databases, embeddings, and semantic retrieval frameworks.
Responsibilities
  • 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.
  • 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.
  • 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, 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.
  • 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, including unit, integration, and regression testing, for complex transformations.
  • Standardize workflow frameworks to enhance operational resilience and performance consistency.
  • 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.
Desired Qualifications
  • Experience operationalizing AI or large-language-model-driven solutions in production data environments is preferred.
  • Strategic systems-thinking and advanced problem-solving capability.
  • Technical authority in structured data and semantic frameworks.
  • Exceptional technical documentation and specification leadership.
  • Strong cross-functional influencing and advisory skills.
  • Governance-driven mindset with an operational excellence focus.
  • Innovation-oriented perspective on practical AI applications.

RELX is a global provider of information-based analytics and decision tools for professionals across scientific, technical, medical, legal, risk, business, and exhibitions industries. It operates in four segments: Scientific, Technical & Medical; Risk & Business Analytics; Legal; and Exhibitions. Its products combine large datasets, analytics, and decision-support tools to help researchers, healthcare professionals, lawyers, and business leaders make informed choices, improve productivity, and achieve better outcomes. Revenue mainly comes from subscriptions, with additional income from transactional sales and advertising. RELX differentiates itself through its deep data assets, specialized industry knowledge, and multi-segment offerings that span content, analytics, and decision-support services. The company pursues a goal of delivering trusted information and insights while supporting corporate responsibility and alignment with the UN SDGs through its products and partnerships.

Company Size

1,001-5,000

Company Stage

IPO

Headquarters

London, United Kingdom

Founded

1894

Get referred to RELX

See people who can refer or advise you

Simplify Jobs

Simplify's Take

What believers are saying

  • RELX grew H1 2026 revenue 7% and adjusted operating profit 9%.
  • RELX announced Doctrine on April 28, 2026, expanding multilingual legal AI across Europe.
  • Risk Solutions and Legal keep hiring; Mike Walsh took Risk CEO on July 1, 2026.

What critics are saying

  • Anthropic-style legal AI tools commoditize research, pressuring LexisNexis pricing during 2026.
  • Doctrine needs EU approvals and integration; failed execution wastes RELX's European AI push.
  • Exhibitions still faces event timing and Middle East disruption, hurting 2026 revenue visibility.

What makes RELX unique

  • RELX combines proprietary datasets with AI workflows across Legal, Risk, STM, and Exhibitions.
  • LexisNexis owns 200 billion legal documents, including Shepard's Citations dating to 1873.
  • Recurring subscriptions and high switching costs protect margins across mission-critical professional workflows.

Help us improve and share your feedback! Did you find this helpful?

Benefits

Health Insurance

Dental Insurance

Vision Insurance

Life Insurance

Disability Insurance

401(k) Retirement Plan

401(k) Company Match

Wellness Program

Mental Health Support

Family Planning Benefits

Health Savings Account/Flexible Spending Account

Flexible Work Hours

Remote Work Options

Company News

Citybiz
Apr 28th, 2026
RELX to Acquire Legaltech Platform Doctrine in European AI Push

RELX Group has entered into an agreement to acquire French legal technology company Doctrine, a move that would expand its... Read More

Business Insider
Mar 1st, 2026
LexisNexis CEO dismisses AI threat as company reports 7% revenue growth

LexisNexis CEO Sean Fitzpatrick has dismissed investor concerns that AI threatens the legal software giant, saying proprietary data gives it a competitive advantage. Shares of parent company Relx fell 14% on 3 February following Anthropic's launch of an AI agent that drafts legal briefs, and are down 17% year-to-date. Fitzpatrick said LexisNexis's database of 200 billion legal documents, including content from Shepard's Citations dating to 1873, cannot be replicated by AI model makers. The company doesn't license its proprietary data to general-purpose AI providers. Relx reported 7% revenue growth for 2025 and 9% increase in adjusted operating profit, driven by customers adopting AI tools. LexisNexis is hiring and hasn't conducted AI-related redundancies.

Yahoo Finance
Feb 22nd, 2026
RELX's LexisNexis launches AI-powered identity management platform for healthcare

LexisNexis Risk Solutions, a wholly owned subsidiary of RELX, has launched a new identity management platform for the healthcare sector. Announced on 19 February, the tool combines identity verification, matching and enrichment capabilities with AI-powered authentication to enhance security throughout patients' healthcare journeys. The platform integrates LexisNexis IDVerse and offers enhanced identity verification, resolution and fraud protection. For healthcare professionals, it accelerates onboarding processes, automates processing and provides digital checks to prevent fraud. RELX is a global information and analytics company serving professional and business customers across scientific, technical, medical, legal and risk management markets.

PR Newswire
Jun 4th, 2025
Elsevier Unveils Rigorous Evaluation Framework To Mitigate Risk In Generative Ai Clinical Decision Support Tools

Clinician-centered framework will be featured in upcoming issue of the Open AccessJournal of the American Medical Informatics Association (JAMIA)Initial evaluations of ClinicalKey AI show high accuracy and usefulness in responses amongst cliniciansNEW YORK, June 4, 2025 /PRNewswire/ -- Elsevier, a global leader in medical information and data analytics, unveiled a groundbreaking evaluation framework for assessing the performance and safety of generative AI-powered clinical reference tools. This innovative approach has been developed for all Elsevier Health generative AI solutions, including ClinicalKey AI, Elsevier's advanced clinical decision support platform, and sets a new standard for responsible AI integration in healthcare. It will be featured in a future issue of the Open Access Journal of the American Medical Informatics Association (JAMIA).The framework, designed with input from clinical subject matter experts across multiple specialties, evaluates AI-generated responses along five critical dimensions: query comprehension, response helpfulness, correctness, completeness, and potential for clinical harm. It serves as a comprehensive assessment to ensure that AI-powered tools not only provide accurate and relevant information but also align with the practical and current needs of healthcare professionals at the point of care.Omry Bigger, President of Clinical Solutions at Elsevier: "This evaluation framework not only supports innovation and advancements to improve patient care but adds an extra layer of review and assessment to ensure physicians are armed with the most accurate information possible. It's a critical step in the implementation of responsible AI for healthcare providers and patients."In a recent evaluation study of ClinicalKey AI, Elsevier worked with a panel of 41-board certified physicians and clinical pharmacists to rigorously test responses generated by the tool for a diverse set of clinical queries. That panel evaluated 426 query-response pairs, and results demonstrated impressive performance, with 94.4% of responses rated as helpful, 95.5% assessed as completely correct, with just 0.47% flagged for potential improvements.Leah Livingston, Director of Generative AI Evaluation for Health Markets at Elsevier, said: "These results reflect not just strong performance, but the real value of bringing clinicians into the evaluation process

PharmiWeb
May 7th, 2025
Elsevier Adds Half A Million Records From Clinicaltrials.Gov To Embase, Enabling A Seamless Search Experience In The World’S Most Comprehensive Biomedical Database

London, 6 May 2025 – Elsevier, a global leader in information and analytics, is announcing the addition of half a million records from ClinicalTrials.gov to its leading biomedical literature database, Embase. The integration will enable researchers to seamlessly view high-quality information on clinical research studies and their results alongside the peer-reviewed literature, in-press publications and conference abstracts already available in Embase. Researchers will be able to conduct more comprehensive evidence and literature searches while having the confidence they will never miss important updates relevant to their drug, therapy, or medical device. Clinical trials data is a vital component of biomedical literature search, helping pharmaceutical and medical device companies stay informed about the latest scientific advancements, regulatory requirements, and competitive insights to support evidence-based decision-making. However, gathering data from multiple sources is currently prone to errors and is time-consuming, such as the duplication of search results, which slows research and regulatory processes. As new therapies and devices are developed and RD organizations seek collaborative partners, they must undertake thorough searches and justifications of evidence