Lead AI Scientist, Document Understanding & Knowledge Graphs

Thomson Reuters Corp.; Zug; Hybrid; CHF 170,000 - 250,000; Full time

Benefits offered by this job

Hybrid Work Model

Flex My Way

Two Mental Health Days off

Headspace app access

Retirement savings

Tuition reimbursement

Employee incentive programs

Two paid volunteer days off annually

Job summary

Thomson Reuters Corp. in Zug (Switzerland) or London (UK) seeks a Lead Applied Scientist, Document Understanding to drive production-grade AI for legal, tax, and accounting content.

You will design semantic chunking, document enrichment, classification, information extraction, and knowledge graph systems powering search, retrieval, reasoning, and agentic workflows. You will mentor scientists, influence AI strategy, and collaborate with engineering teams to deliver scalable, reliable solutions

Qualifications

• PhD in CS, AI, NLP, ML, IR with post-degree industry experience.

Responsibilities

• Design and deploy semantic chunking systems for lengthy legal, tax, and accounting documents.
• Build document enrichment pipelines to identify document types, jurisdictions, concepts, entities, and metadata.
• Develop multi-label classification systems using standard and customer taxonomies.
• Build NLP information extraction pipelines for entities, relationships, citations, and key concepts.
• Create knowledge graph construction to connect and enrich entities and concepts across large collections.
• Design systems to interpret and extract insights from complex tabular data embedded in documents.
• Create document intelligence capabilities to support downstream search, retrieval, RAG and agentic AI workflows.
• Lead architectural decisions and mentor applied scientists across the organization.

Education

PhD in Computer Science, AI, NLP, or related field

Job description

Thomson Reuters Corp. in Zug (Switzerland) or London (UK) seeks a Lead Applied Scientist, Document Understanding to drive production-grade AI for legal, tax, and accounting content.

You will design semantic chunking, document enrichment, classification, information extraction, and knowledge graph systems powering search, retrieval, reasoning, and agentic workflows. You will mentor scientists, influence AI strategy, and collaborate with engineering teams to deliver scalable, reliable solutions