Applied AI Data Scientist

Company: RELX

Location: New York, NY (Remote)

Salary: $132.7k - $221.1k per year

Type: Full-time

Remote: Yes

Posted: 2026-08-22

About this role

  • Please note that this position will be located in New York City and will require full-time, on-site presence. If you are unable to align with this requirement, please consider other roles across LexisNexis that might allow for hybrid and/or remote work.\*\*

Do you want to help us build further data science capabilities?


And are you eager to work on the quality of data sources serving our end-user products?


About Our Team
LexisNexis Legal & Professional, which serves customers in more than 150 countries with 11,300 employees worldwide, is apart of RELX, a global provider of information-based analytics and decision tools for professional and business customers.


About The Role
LexisNexis Legal & Professional is hiring an Applied AI Data Scientist to help shape the next generation of AI-powered legal products and experiences.


As an Applied AI Data Scientist at LexisNexis, you will partner with internal teams and enterprise stakeholders to design, evaluate, and continuously improve the AI capabilities that power legal research, drafting, and decision-making. You will work directly with AI engineers, machine learning engineers, and product teams to frame problems, run experiments, design evaluation methodologies, and turn applied research into production-ready AI features that support complex legal and professional workflows.


This role sits at the intersection of AI experimentation, developer enablement, evaluation, and customer engagement. You will partner closely with the Applied AI Engineer and the broader Product, Engineering, and AI Platform teams — bringing the data science lens to model selection, retrieval quality, prompting strategy, and measurement so the team builds the right things and knows when they are working.


This is a deeply hands-on role focused on experimentation, evaluation, prototyping, and iterating on AI-powered experiences. The ideal candidate combines strong applied data science and machine learning ...

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