Senior Data Scientist III

About the Team LexisNexis Legal & Professional, which serves customers in more than 150 countries with 11,800 employees worldwide, is part of RELX, 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. About the Role Senior Data Scientist III are emerging subject matter experts in their domain, who define projects and their execution. While they may have small teams of indirect reports, they lead through influence and their focus is on mentoring teams to develop and execute on best practices and methodologies. Responsibilities Lead experimentation and model development for AI/ML solutions in legal products. Design and evaluate NLP, LLM, and generative AI approaches (e.g., RAG, prompt strategies). Define agentic workflows and reasoning strategies for multi‑step legal tasks. Define 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. Required Qualifications Bachelor’s or Master’s degree in a relevant field (e.g., Computer Science, Data Science, Statistics, Mathematics). Strong experience in NLP and LLM‑based modeling. Strong experience with generative AI techniques (e.g., prompt engineering, RAG). Experienced in designing and evaluating hybrid search (semantic + lexical) using embeddings and vector databases. Experience designing 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. Ability to define retrieval strategies, including hybrid search (semantic + lexical), and evaluation metrics (e.g., relevance, ranking quality). Able to analyze large‑scale legal datasets to extract insights and improve model performance. U.S. National Base Pay Range: $115,400 - $192,300. Geographic differentials may apply in some locations to better reflect local market rates. Base Pay Ranges for specific states: Colorado: $115,400 - $192,300 Illinois: $121,200 - $201,900 Chicago, IL: $126,900 - $211,500 Maryland: $121,200 - $201,900 New York: $126,900 - $211,500 New York City: $138,400 - $230,700 Rochester, NY: $115,400 - $192,300 Ohio: $109,500 - $182,700 New Jersey: $130,284 - $208,116 This job is eligible for an annual incentive bonus. EEO Statement 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. #J-18808-Ljbffr