Lead Applied Scientist, Document Understanding

Thomson Reuters is seeking a Lead Applied Scientist, Document Understanding to join their team in Zug, Switzerland or London, UK. This role offers a unique opportunity to leverage your expertise in building document understanding AI solutions to enhance leading products in the tax, legal, and professional services industries.

Document understanding is a critical intelligence layer powering major capabilities across their legal AI platform. You will be instrumental in building state-of-the-art systems for semantic chunking, document enrichment, and knowledge graph construction, serving as the cognitive foundation for multiple product teams. This position offers immediate production impact, shaping how millions of legal professionals research and analyze complex legal documents.

Join Thomson Reuters to solve publishing-quality research problems and advance the capabilities for the next generation of intelligent legal AI agents. Apply now to make a significant contribution!

Company Overview

Thomson Reuters (TSX/NDAQ: TRI) is a global leader in providing trusted content and technology that empowers professionals across legal, tax, accounting, compliance, government, and media industries. Their products combine specialized software and insights to enable informed decision-making and support institutions in their pursuit of justice, truth, and transparency. Reuters, a part of Thomson Reuters, is a world-leading provider of trusted journalism and news.

With 26,000 employees across more than 70 countries, Thomson Reuters is committed to fostering flexible work environments where everyone can contribute and grow. They are dedicated to objectivity, accuracy, fairness, and transparency, and they value the unique backgrounds, perspectives, and experiences of all employees.

Quick Details

• Salary Range: Not Applicable
• Job Type: Full-time
• Qualifications: PhD in Computer Science, AI, NLP, Machine Learning, Information Retrieval, or a related field, with demonstrable post-degree industry experience
• Experience: 5 Year+

Key Responsibilities

• Design and deploy semantic chunking systems for lengthy, non-uniformly structured legal, tax, and accounting documents.
• Build document enrichment pipelines to 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 to 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.

Requirements

• 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.

Benefits

• Hybrid Work Model: Flexible hybrid working environment with seamless digital and physical connection.
• Flexibility & Work-Life Balance: Flex My Way policies, including work from anywhere for up to 8 weeks per year.
• Career Development and Growth: Continuous learning, skill development, and Grow My Way programming.
• Industry Competitive Benefits: Comprehensive benefit plans including flexible vacation, mental health days, Headspace app access, retirement savings, tuition reimbursement, and employee incentive programs.
• Culture: Globally recognized reputation for inclusion, belonging, flexibility, and work-life balance, guided by company values.
• Social Impact: Opportunities to make an impact through two paid volunteer days off annually and involvement in pro-bono consulting and ESG initiatives.
• Making a Real-World Impact: Help customers pursue justice, truth, and transparency, uphold the rule of law, turn the wheels of commerce, and provide trusted information globally.