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Thomson Reuters

Applied Scientist, Search

London
Posted about 20 hours ago
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This position is based in either Zug, Switzerland or London, UK.

Want to use your experience of building search-led AI solutions to enhance our leading products in the tax, legal and professional services industries?

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. In this new role, 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.

About The Role

As an Applied Scientist at Thomson Reuters, you will:

  • Innovate & Deliver: Design, build, test, and deploy end-to-end AI solutions for complex document understanding tasks in the legal domain.

  • Develop advanced models for semantic chunking of lengthy, non-uniformly structured legal documents with adjustable granularity levels for different use cases.

  • Build document enrichment systems that classify documents according to legal and customer-defined taxonomies and extract rich metadata.

  • Create LLM-based knowledge graph construction pipelines that extract and link heterogeneous legal knowledge including citations, entities, and legal concepts across diverse legal content.

  • Develop scalable synthetic data generation systems to support model training, simulate complex legal research queries and generate hallucination-free answers.

  • Work in collaboration with engineering to ensure well-managed software delivery and reliability at scale.

  • Evaluate & Optimize: Develop comprehensive data and evaluation strategies for both component-level and end-to-end quality, leveraging expert human annotation and synthetic data generation.

  • Apply robust training and evaluation methodologies that balance model performance with latency requirements, particularly for SLM-based solutions. You'll apply knowledge distillation techniques to compress large models into efficient SLMs suitable for production deployment.

  • Drive Technical Decisions: Independently determine appropriate architectures for challenging document understanding problems including: semantic chunking strategies that handle diverse document formats, preserve legal document structure, and adapt to different granularity needs; document classification approaches that work across varying legal taxonomies and generalize to customer-defined schemas; LLM-based knowledge extraction methods that handle challenges like citation recognition errors and contextual references; multi-document reasoning architectures for generating synthetic multi-hop queries that reflect complex legal research patterns.

  • Balance accuracy, efficiency, and scalability while solving real-world challenges like handling diverse document formats and content types.

  • Align & Communicate: Partner closely with Engineering and Product teams to translate complex legal document understanding challenges into scalable, production-ready solutions.

  • Engage stakeholders across multiple product lines to deeply understand use case requirements, shaping objectives that align document understanding capabilities with diverse business needs including next-generation search and deep legal research.

Reasons to use Rodeo

I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?

Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.

Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.

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Graduate Consultant — 2026 Scheme

PwC·London, UK
£35,000/yr

Why you're a good match

Strong

Your economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.

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Why you're a good match

You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.

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Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.

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  • Advance the Field: Maintain scientific and technical expertise in one or more relevant areas as demonstrated through product deliverables, published research at top venues (e.g., ACL, EMNLP, ICLR, NeurIPS, SIGIR, KDD), and intellectual property.

About You

You're a fit for the role of Applied Scientist if you have:

  • PhD in Computer Science, AI, NLP, or a related field, or a Master's with equivalent research/industry experience
  • Demonstrable hands-on experience building and deploying document understanding systems, information extraction pipelines and knowledge distillation, or knowledge graph construction using deep learning, LLMs and NLP methods.
  • Solid understanding of synthetic data generation techniques for NLP, including query - answer generation with verification and scalable data augmentation for training specialized models
  • Deep understanding of document understanding fundamentals: document layout analysis, semantic chunking approaches beyond fixed-size or paragraph-based methods, document classification handling hierarchical taxonomies, imbalanced multi-label classification, and adapting to domain-specific schemas.
  • Proven ability to translate complex document understanding problems into innovative AI applications that balance accuracy and efficiency
  • Professional experience scaling yourself and leading through others, in an applied research setting
  • Strong programming skills (e.g., Python) and experience with modern deep learning frameworks (e.g., PyTorch, Hugging Face Transformers, DeepSpeed)
  • Publications at relevant venues such as ACL, EMNLP, ICLR, NeurIPS, SIGIR, KDD
  • Solid understanding of DL/ML approaches used for NLP tasks
  • Experience designing annotation workflows, creating high-quality labeled datasets with clear guidelines, and developing evaluation frameworks for document understanding tasks.

What’s in it For You?

  • Hybrid Work Model: We’ve adopted a flexible hybrid working environment (2-3 days a week in the office depending on the role) 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.

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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.

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More information about Thomson Reuters can be found on thomsonreuters.com

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Skills

Natural Language Processing
Large Language Models
Knowledge Graph Construction
Semantic Chunking
Information Extraction
Knowledge Distillation
Synthetic Data Generation
Python
PyTorch
Hugging Face Transformers
DeepSpeed
Document Layout Analysis
Deep Learning
Machine Learning
Model Evaluation
Multi-document Reasoning

Location

London, England, United Kingdom

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