RELXSenior Data Scientist II
AI in this role
About the Team:
LexisNexis Legal & Professional, which serves customers in more than 150 countries with 11,800 employees worldwide, is part of RELX (www.relx.com), a global provider of information-based analytics and decision tools for professional and business customers. Our company has been a long-time leader in deploying AI and advanced technologies to the legal market to improve productivity and transform the overall business and practice of law, deploying ethical and powerful generative AI solutions with a flexible, multi-model approach that prioritizes using the best model from today’s top model creators for each individual legal use case. The company employs over 2,000 technologists, data scientists, and experts to develop, test, and validate solutions in line with RELX Responsible AI Principles (https://stories.relx.com/responsible-ai-principles/index.html).
About the Role:
Are you looking to develop your Data Scientist career?
Would you enjoy training more junior team members?
We are seeking a Senior Data Scientist II to help lead the design and validation of AI-driven product capabilities within the legal domain. This team is global AI platform team that builds AI products and ships AI features to production. The team works on cutting edge AI technology and extensively leverages latest AI tools/Features as part of product.
Responsibilities:
Develop and implement NLP, LLM, and generative AI approaches (e.g., RAG, prompt strategies).
Define agentic workflows and reasoning strategies for multi-step legal tasks.
Develop retrieval strategies, including hybrid search (semantic + lexical), and evaluation metrics (e.g., relevance, ranking quality).
Analyze large-scale legal datasets to extract insights and improve model performance.
Establish best practices for model evaluation, validation, and benchmarking.
Translate experimental results into clear product recommendations and business impact.
Collaborate with product, legal experts, and engineers to align solutions with user needs.
Mentor team members and provide technical leadership in data science and AI.
Requirements:
Master’s degree or above in a quantitative or technical field (Statistics, Computer Science, Mathematics, Data Science, etc.).
Strong experience in machine learning, NLP, and LLM-based modeling.
Strong experience designing and running experiments, including model evaluation and iteration.
Experience with generative AI techniques (e.g., prompt engineering, RAG).
Experience designing and evaluating hybrid search (semantic + lexical) using embeddings and vector databases.
Experience designing agentic workflows and reasoning strategies, with hands-on experience applying agent frameworks (e.g., LangChain, LangGraph, AutoGen) in real-world use cases.
Proficiency in Python and data analysis tools.
Strong foundation in statistics, modeling, and large-scale text processing.
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USA Job Seekers:
How we rate this
Senior Data Scientist II at RELX rates 96 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- How do you structure and test a prompt to get consistent output from a language model?
- How would you design a retrieval step so the model answers from real data instead of guessing?
- How do you decide when an AI agent can act on its own versus asking for approval first?
- How do you decide that one model's output is better than another's for a given task?
- What NLP problem have you worked on, and how did you measure whether it actually worked?
Adapt your resume
- List these exact terms on your resume: Prompt Engineering, RAG, AI Agents, AI Evaluation, and NLP. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.
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