Senior Applied Scientist, Graphs and ML

Position: Senior Applied Scientist, Knowledge Graphs and ML
Location: Indiana

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** Senior Applied Scientist, Knowledge Graphs and ML
**** This hybrid position will be based in Zug, Switzerland.
**** Thomson Reuters Labs
** are seeking
** applied data scientists
** with experience of using
** knowledge graphs
** and ML, to drive the capabilities of Thomson Reuters’ suite of products, with a particular focus on those serving risk and fraud.

So what does
** Thomson Reuters Labs
** including CLEAR, CLEAR Adverse Media and CLEAR Risk Inform.
** Thomson Reuters CLEAR
** helps public and private sector organisations (from financial services firms to law enforcement, child and family services to manufacturing) make confident decisions at pace, analysing the connections of people and entities as part of their investigations.

As
** Senior Applied Scientist, Knowledge Graphs and ML**, you will act as a researcher that drives innovation at the intersection of knowledge representation and modern AI. You'll spend your time exploring uncharted territory—designing experiments, testing hypotheses, and discovering what's possible when you combine knowledge graphs, graph algorithms, NLP, and GenAI in novel ways. We're looking for someone who thinks like a scientist but can use their experience of working with real-world data at scale - someone who knows which techniques from papers actually work in practice and can use this to design experiments that generate actionable insights, not just interesting findings.
** About the Role
** As a
** Senior Applied Scientist**, you will**:
*** Be a knowledge graph / ontology / semantic web and NLP expert. You’ll design and execute experiments that answer critical research questions, balancing scientific rigour with business impact.
* Explore the frontier of graph ML, RAG architectures, and agentic AI—testing new algorithms, architectures, and techniques to see what delivers value
* Own and manage end-to-end knowledge graph experimentation and development—from ontology design and data ingestion to graph algorithms and AI-powered applications—guiding others in research, data engineering, and evaluation
* Operate in an agile way, pushing for quick iterations guided by customers' needs
* Be accountable for all research deliverables on small to medium-sized projects involving knowledge graphs and graph-based AI solutions
* Work with stakeholders to define scope, determine feasibility, and translate business/customer objectives into technical requirements
* Partner effectively with Engineering to ensure well-managed software delivery and co-design ML Ops processes
* Support and coach junior scientists by providing advice, mentoring, and training on knowledge graph best practices and NLP techniques
** About You
** You’re a fit for the role of
** Senior Applied Scientist
** if your background includes:
* PhD in a relevant discipline or Master’s plus a comparable level of research experience
* Demonstrable hands-on industry experience (post-PhD) building NLP / ML / Knowledge Graph / GenAI systems for commercial applications
* Experience investigating knowledge graph design and construction, graph-based reasoning, and graph-ML—with a practical understanding of what works at scale
* Deep knowledge of modern NLP methods and active experimentation with GenAI techniques (RAG, prompt engineering, agentic frameworks)
* Experience writing production code and ensuring well-managed software delivery
* Demonstrable experience translating complex problems into successful AI applications
* Outstanding communication, problem-solving, and analysis skills
* Collaborating with Product, Engineering and Business Stakeholders in an agile manner to demonstrate value and iterate with customer feedback
* Experience working with real-world, messy data in commercial/industry contexts (not just clean benchmark datasets)
* Excellent coding skills in Python, proficiency with Git and cloud technologies
*
* Please Note:

Complete applications must be submitted by 23:59 (GMT) on Sunday 11th January 2026. Early applications are encouraged.**#LI-JB2
* ** Hybrid Work Model:
** We’ve adopted a flexible hybrid working environment (2-3…