Lead Applied Scientist, Document Understanding

Thomson Reuters

Greater London

Hybrid

GBP 140,000 - 190,000

Full time

18 hours ago
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Benefits offered by this job

Hybrid Work Model
Flexible work arrangements
Career development programs
Mental health days

Job summary

Thomson Reuters is seeking a Lead Applied Scientist in Document Understanding to advance our legal, tax, and accounting AI platforms. You will design semantic chunking, enrichment, classification, and knowledge graph systems powering search, retrieval, and generative experiences across millions of documents.

You will mentor scientists, guide production deployments, and collaborate with product teams to shape technology strategy and roadmaps for the next generation of intelligent legal AI agents.

Qualifications

  • PhD in Computer Science, AI, NLP, Machine Learning, Information Retrieval, or a related field, with demonstrable post-degree industry experience developing and deploying document understanding systems at scale.
  • Experience of building production document understanding systems that go beyond basic OCR or document parsing and deliver measurable business impact.
  • Hands-on depth across document analysis, information extraction, classification, knowledge representation, evaluation, and production deployment.
  • Successfully taken advanced NLP and AI capabilities from research through production and understand how to transform complex, unstructured content into structured knowledge that powers search, retrieval, reasoning, and intelligent workflows.

Responsibilities

  • Design and deploy semantic chunking systems for lengthy, non-uniformly structured legal, tax, and accounting documents.
  • Build document enrichment pipelines that identify document types, jurisdictions, legal concepts, entities, parties, and other domain-specific metadata.
  • Develop hierarchical and multi-label document classification systems using both standard and customer-defined taxonomies.
  • Build LLM-based and traditional NLP information extraction pipelines that identify entities, relationships, citations, references, and key concepts from unstructured content.
  • Develop knowledge graph construction systems that extract, normalize, connect, and enrich entities, legal concepts, citations, and relationships across large document collections.
  • Design systems that identify, interpret, and extract insights from complex tabular data embedded within legal, tax, regulatory, and accounting documents.
  • Create document intelligence capabilities that support downstream search, retrieval, RAG, and agentic AI workflows.
  • Design robust evaluation frameworks for document understanding systems using expert annotations, synthetic datasets, and production metrics.
  • Lead technical decisions on document analysis architectures, chunking strategies, extraction methodologies, classification approaches, and knowledge representation frameworks.
  • Partner closely with engineering teams to deliver scalable, reliable, and production-ready AI systems.
  • Provide technical leadership and input into AI strategy, platform capabilities, and long-term roadmap decisions.
  • Mentor applied scientists and machine learning practitioners across the organization.

Job description

Lead Applied Scientist, Document Understanding

This position is based in either Zug, Switzerland or London, UK. Want to use your experience of building document understanding AI solutions to enhance our leading products in the tax, legal and professional services industries?

Job Description

Lead Applied Scientist, Document Understanding

Document understanding

Document understanding is a foundational intelligence layer that powers every major capability across our legal AI platform—from search and information extraction to agentic reasoning in products like Westlaw, PracticalLaw, and CoCounsel. You'll build state-of-the-art semantic chunking, document enrichment, and knowledge graph construction systems that serve as the cognitive foundation multiple product teams depend on, working across authoritative legal, tax, and accounting content and extraordinarily diverse customer data. This is a rare opportunity to solve publishing-quality research problems with immediate production impact—your innovations will directly shape how millions of legal professionals research, analyze, and reason over complex legal documents while advancing the capabilities that enable the next generation of intelligent legal AI agents. You will work across semantic chunking, document enrichment, intelligent classification, information extraction, knowledge graph construction, and tabular data understanding for complex legal, tax, and accounting content. This work forms the foundation for downstream search, retrieval, reasoning, and generative AI experiences.

Key Responsibilities
  • Design and deploy semantic chunking systems for lengthy, non-uniformly structured legal, tax, and accounting documents
  • Build document enrichment pipelines that identify document types, jurisdictions, legal concepts, entities, parties, and other domain-specific metadata
  • Develop hierarchical and multi-label document classification systems using both standard and customer-defined taxonomies
  • Build LLM-based and traditional NLP information extraction pipelines that identify entities, relationships, citations, references, and key concepts from unstructured content
  • Develop knowledge graph construction systems that extract, normalize, connect, and enrich entities, legal concepts, citations, and relationships across large document collections
  • Design systems that identify, interpret, and extract insights from complex tabular data embedded within legal, tax, regulatory, and accounting documents
  • Create document intelligence capabilities that support downstream search, retrieval, RAG, and agentic AI workflows
  • Design robust evaluation frameworks for document understanding systems using expert annotations, synthetic datasets, and production metrics
  • Lead technical decisions on document analysis architectures, chunking strategies, extraction methodologies, classification approaches, and knowledge representation frameworks
  • Partner closely with engineering teams to deliver scalable, reliable, and production-ready AI systems
  • Provide technical leadership and input into AI strategy, platform capabilities, and long-term roadmap decisions
  • Mentor applied scientists and machine learning practitioners across the organization
Required Qualifications
  • PhD in Computer Science, AI, NLP, Machine Learning, Information Retrieval, or a related field, with demonstrable post-degree industry experience developing and deploying document understanding systems at scale.
  • Experience of building production document understanding systems that go beyond basic OCR or document parsing and deliver measurable business impact.
  • Hands-on depth across document analysis, information extraction, classification, knowledge representation, evaluation, and production deployment.
  • Successfully taken advanced NLP and AI capabilities from research through production and understand how to transform complex, unstructured content into structured knowledge that powers search, retrieval, reasoning, and intelligent workflows.
Preferred Qualifications
  • A collaborative mindset where you can mentor and measure success by what ships and performs in production.
  • An understanding of how to transform large collections of unstructured documents into structured knowledge assets, building knowledge graphs from real-world content and using them to improve retrieval, reasoning, and AI workflows and extracting meaningful insights from both natural language and complex tabular content.
What’s in it For You?
  • Hybrid Work Model: We’ve adopted a flexible hybrid working environment for our office-based roles while delivering a seamless experience that is digitally and physically connected.
  • Flexibility & Work-Life Balance: Flex My Way is a set of supportive workplace policies designed to help manage personal and professional responsibilities, whether caring for family, giving back to the community, or finding time to refresh and reset. This builds upon our flexible work arrangements, including work from anywhere for up to 8 weeks per year, empowering employees to achieve a better work-life balance.
  • Career Development and Growth: By fostering a culture of continuous learning and skill development, we prepare our talent to tackle tomorrow’s challenges and deliver real-world solutions. Our Grow My Way programming and skills-first approach ensures you have the tools and knowledge to grow, lead, and thrive in an AI-enabled future.
  • Industry Competitive Benefits: We offer comprehensive benefit plans to include flexible vacation, two company-wide Mental Health Days off, access to the Headspace app, retirement savings, tuition reimbursement, employee incentive programs, and resources for mental, physical, and financial wellbeing.
  • Culture: Globally recognized, award-winning reputation for inclusion and belonging, flexibility, work-life balance, and more. We live by our values: Obsess over our Customers, Compete to Win, Challenge (Y)our Thinking, Act Fast / Learn Fast, and Stronger Together.
  • Social Impact: Make an impact in your community with our Social Impact Institute. We offer employees two paid volunteer days off annually and opportunities to get involved with pro-bono consulting projects and Environmental, Social, and Governance (ESG) initiatives.
  • Making a Real-World Impact:We are one of the few companies globally that helps its customers pursue justice, truth, and transparency. Together, with the professionals and institutions we serve, we help uphold the rule of law, turn the wheels of commerce, catch bad actors, report the facts, and provide trusted, unbiased information to people all over the world.
DISCLAIMER

The above information in this description has been designed to indicate the general nature and level of work performed by employees within this classification. It is not designed to contain or be interpreted as a comprehensive inventory of all duties, responsibilities, and qualifications required of employees assigned to this job.

About Us

Thomson Reuters informs the way forward by bringing together the trusted content and technology that people and organizations need to make the right decisions. We serve professionals across legal, tax, accounting, compliance, government, and media. Our products combine highly specialized software and insights to empower professionals with the data, intelligence, and solutions needed to make informed decisions, and to help institutions in their pursuit of justice, truth, and transparency. Reuters, part of Thomson Reuters, is a world leading provider of trusted journalism and news. We are powered by the talents of 26,000 employees across more than 70 countries, where everyone has a chance to contribute and grow professionally in flexible work environments. At a time when objectivity, accuracy, fairness, and transparency are under attack, we consider it our duty to pursue them. Sound exciting? Join us and help shape the industries that move society forward. As a global business, we rely on the unique backgrounds, perspectives, and experiences of all employees to deliver on our business goals. To ensure we can do that, we seek talented, qualified employees in all our operations around the world regardless of race, color, sex/gender, including pregnancy, gender identity and expression, national origin, religion, sexual orientation, disability, age, marital status, citizen status, veteran status, or any other protected classification under applicable law. Thomson Reuters is proud to be an Equal Employment Opportunity Employer providing a drug-free workplace. We also make reasonable accommodations for qualified individuals with disabilities and for sincerely held religious beliefs in accordance with applicable law. More information on requesting an accommodation here. Learn more on how to protect yourself from fraudulent job postings here. More information about Thomson Reuters can be found on thomsonreuters.com

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