Senior Data Scientist / Machine Learning Scientist

Overview

About our Team: LexisNexis Legal & Professional, serving customers in over 150 countries with 11,800 employees worldwide, is part of RELX, a global provider of customers. Our company is a leader in deploying AI and advanced technologies to improve productivity and transform the legal market. best models from today’s top creators for each legal use case. We are seeking a Senior Data Scientist II to help lead the design and validation of Agentic AI-driven product capabilities within the legal domain. focuses on defining what to build and why—leveraging machine learning, NLP, and large language models (LLMs) to solve complex legal workflows.

You will help engineers to translate validated approaches into scalable, customer-facing Responsibilities: Develop and implement NLP, LLM, and generative AI reasoning strategies for multi-step legal tasks. relevance, ranking quality). Analyze large-scale legal datasets to extract insights and improve model performance. legal experts, and engineers to align solutions with user needs. members and provide technical leadership in data science and AI. Master’s degree or above in a quantitative or technical field (Statistics, Computer Science, Mathematics, Data Science, etc.).

experience in machine learning, NLP, and LLM-based modeling. Strong coding skills.

Experience with generative AI techniques (e.g., lexical) using embeddings and vector databases. Proficiency in Python and data analysis tools. Strong foundation in statistics, 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 multi-carrier program for medical, dental and vision benefits Retirement Wellness platform with incentives, Headspace app subscription, Employee Assistance and Time-off Programs Short-and-Long Term Disability, Life and Accounts Up to two days of paid leave each to participate in Employee Resource LexisNexis Legal & Professional® provides legal, regulatory, and business information and analytics that help customers increase their productivity, As a digital pioneer, the company was the first to bring legal and business information online with its Lexis® and Nexis® services. #apply in some locations to better reflect local market rates. Colorado, the base pay range is $104,900 – $174,700.the base pay range is $110,100 – $183,500.If performed in Maryland, the base pay range is $If performed in New York, the base pay range is $115,400 – $If performed in New York City, the base pay range is $125,900 – $If performed in Rochester, NY, the base pay range is $104,900 – $If performed in New Jersey, the base pay range is $118,349 – $If performed in Ohio, the base pay range is $99,700 – $166,000. job is eligible for an annual incentive bonus. Application deadline is If you have a disability or other need pose as recruiters asking for money or personal information.

Please read our Candidate Privacy Policy. citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other LexisNexis Legal & Professional is a leading global provider of legal, regulatory and business information and analytics that help customers increase productivity, improve decision-making and outcomes, and advance the rule of law We help lawyers win cases, manage their work more efficiently, their supply chains. We partner with leading global associations and customers to help collect evidence against war criminals and provide tools to combat human are combining unparalleled legal and business information with analytics and technology to advance what’s possible for the way our customers work and to

Company:

Reed Technology

Qualifications:

Language requirements:

Specific requirements:

Educational level:

Level of experience (years):

Senior (5+ years of experience)

Tagged as: Data Analysis, Industry, Language Modeling, Machine Learning, NLP, United States