Position: Data Scientist – Natural Language Processing (NLP)

Location: Bonn (hybrid)

Fulltime

About the Role

LexisNexis Intellectual Property Solutions is seeking a highly skilled NLP Expert with proven expertise in semantic embeddings and knowledge graphs. This is a research-driven, hands-on role where you will design, build, and optimize language technologies that transform how customers search, analyze, and interact with intellectual property (IP) data.

About the Team

You will join a collaborative team of data scientists, AI engineers, and domain experts to push the boundaries of how semantic representations and graph-based reasoning can enhance search, discovery, and predictive insights in the IP domain.

At LexisNexis, we value curiosity, innovation, and collaboration. You will be part of a vibrant community of data scientists and AI engineers.

Responsibilities:

• Apply state-of-the-art techniques in embeddings, transformers, and generative language models to IP data.

• Design and enhance knowledge graph architectures to capture domain knowledge and enable advanced reasoning.

• Integrate embeddings and NLP methods with graph-based systems to power knowledge-driven insights.

• Prototype and validate new approaches, transitioning successful methods into production-grade systems in collaboration with AI engineering teams.

• Stay current with state-of-the-art NLP and graph research, applying and adapting new methods to real-world problems in intellectual property.

• Contribute to the internal knowledge base by publishing technical reports, presenting at internal forums, and, where appropriate, authoring external publications or patents.

• Work with product managers and business stakeholders to deliver customer-focused solutions with measurable impact.

Qualifications:

• Master’s or PhD in Computer Science, Computational Linguistics, Artificial Intelligence, or related discipline.

• 3+ years of hands-on experience building NLP solutions in a research or commercial environment.

• Proven expertise in modern NLP techniques (e.g., semantic embeddings, transformer architectures, generative models) with experience evaluating, optimizing, and scaling NLP models.

• Strong experience with knowledge graph design, construction, and integration with NLP systems.

• Hands-on skills in Python and modern ML frameworks (e.g., PyTorch, TensorFlow).

• Excellent problem-solving and communication skills, with experience collaborating in cross-functional, agile teams.

Preferred

• Familiarity with graph databases (Neo4j, RDF, SPARQL) and distributed knowledge graph systems.

• Publications, patents, or conference presentations in relevant NLP or ML venues.

Work in a way that works for you
We know that your wellbeing and happiness are key to a long and successful career. We promote a healthy work/life balance across the organisation. We offer an appealing working prospect for our people. With numerous wellbeing initiatives, shared parental leave, study assistance and sabbaticals, we will help you meet your immediate responsibilities and your long-term goals.

• Working flexible hours - flexing the times when you work in the day to help you fit everything in and work when you are the most productive.

About the Business

LexisNexis, a part of RELX, is a leading global provider of legal, regulatory, and business information. We help customers increase productivity and improve decision-making and outcomes. Our 10,500 experts and innovative tools help us shape a better world for our customers and communities.

We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location.

We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-855-833-5120.

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We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law.

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