Sr. Manager Data Science - Gen AI and Content Systems

Overview

Would you like to lead a team building production-grade NLP and LLM capabilities that transform legal and business information into actionable intelligence? Do you enjoy shaping the future of AI and data science in a way that delivers measurable customer and business impact?

Please note : The selected individual for this role will be expected to work in our Raleigh, NC location from the time of joining. If you reside outside of the Raleigh region and you are unable or unwilling to relocate, please consider other roles across our organization that might allow for remote locations.

About our Team : LexisNexis Legal & Professional serves customers in more than 150 countries with 11,800 employees and is part of RELX, a global provider of information-based analytics and decision tools for professional and business customers. The company deploys AI and advanced technologies to the legal market to improve productivity and transform the practice of law, deploying ethical and powerful generative AI solutions with a flexible, multi-model approach. The company employs technologists, data scientists, and experts to develop, test, and validate solutions in line with RELX Responsible AI Principles.

About LexisNexis Data Sciences : We’re redefining legal intelligence through advanced AI. Our teams harness the power of large language models (LLMs), RAG, agentic systems and large-scale content systems to build tools that acquire, structure, enrich and deliver legal content. Join us in building AI systems that help legal professionals move faster, think deeper, and operate with confidence.

Role Overview

We are seeking a hands-on Senior Manager of Data Science to lead a high-impact team in developing the strategy, standards, and execution of AI across our content ecosystem. You will lead a team that embeds machine learning and generative AI directly into production systems operating at scale. This role focuses on balancing innovation with practical constraints (latency, cost, reliability) and rapidly deploying to production environments. It is central to transforming toward an intelligent, agent-enabled content platform capable of grounded reasoning and turning structured and unstructured data sources into legal knowledge.

Key Responsibilities

Scope & Impact

• Set the vision and strategic priorities, acting as a recognized expert for Data Science
• Lead and develop a team of data scientists and ML engineers, setting the cultural tone
• Drive applied research with a clear path to production , balancing innovation against real-world constraints including latency, cost, and reliability
• Build and scale evaluation science capabilities within the team, including offline evaluation frameworks, automated benchmarking pipelines, and human-in-the-loop feedback systems to measure model quality and business impact
• Champion hands-on rapid prototyping and iteration
• Collaborate with other Data Science teams to maximize reuse of components and patterns, eliminating waste, duplication and unnecessary customization
• Coordinate across multiple cross-functional teams, systems, and domains

Technical & Product Leadership

• Collaborate with other Data Science teams to define and execute the AI roadmap across the content lifecycle, maximizing reuse in areas including: Content collection, metadata extraction/enrichment/classification, agentic workflows, and AI-powered downstream capabilities
• Design and deploy scalable, production-grade AI systems, including: LLM-powered document understanding/generation, agentic workflows, retrieval-augmented generation (RAG) pipelines, and hybrid ML + rules-based systems
• Lead through execution with examples: actively writing code, building/demonstrating working prototypes, and contributing to experiments and production models
• Establish and scale best practices in Data Science, including model development/evaluation/monitoring, prompt engineering, data prep and feature standards, and reusable components
• Partner with engineering, architecture, and product leaders to integrate AI into large-scale distributed systems, ensure performance, scalability, reliability, and align technical solutions with business outcomes
• Translate complex problems into clear project plans and executable solutions, and lead teams through delivery
• Present tradeoffs and options when facing delivery constraints

Team & Operational Excellence

• Mentor and grow a multidisciplinary team of LLM-focused Data Scientists and ML Engineers
• Drive cross-functional collaboration with Legal SMEs, Data Engineers, Product Managers, and Design
• Establish best practices for evaluation, observability, and responsible use of generative AI
• Oversee infrastructure to support continuous delivery and monitoring of LLM systems in production

Core Qualifications

Experience & Education

• Advanced degree (Master’s or PhD) in Data Science, Computer Science, Statistics, or a related field strongly preferred, or equivalent practical experience
• Bachelor’s degree with significant applied experience in data science, ML, or AI
• Typically requires: 8+ years of relevant experience in data science, ML, or applied AI; 4+ years of leadership experience

We recognize that exceptional candidates may follow non-traditional paths and value demonstrated impact, technical depth, and leadership over strict credential requirements.

Success in this role requires :

• Leading through technical expertise and organizational influence
• Acting as a change agent, embedding best practices into workflows and systems
• Driving team development and strategic outcomes across a broad scope
• Ability to select the right tools and technologies to solve business problems

Technical Proficiency

• Proficient with Python, ML and LLM tooling such as Google ADK, LangChain, ML Frameworks (TensorFlow, PyTorch) and prompt tuning
• Familiarity with vector databases, knowledge graphs, and hybrid retrieval architecture
• Strong experience with structured and unstructured data at scale
• Ability to design and implement data pipelines
• Experience integrating ML into complex, multi-stage processing systems
• Working knowledge of containerization, CI/CD, RESTful API design and model serving tools
• Cloud infrastructure experience on AWS (preferred), Azure, or GCP
• Familiarity with AI coding tools

Preferred Background

• Graduate degree in CS/AI/ML or equivalent experience
• 8+ years post-degree experience, with 4+ years in data science or applied AI leadership focused on NLP/LLM
• Prior experience in legal tech or document-intensive domains is desirable
• Familiarity with ethical/legal considerations in deploying generative AI in professional settings

Work Preferences

We promote a healthy work/life balance with flexible hours and wellbeing initiatives. Benefits include parental leave, study assistance and sabbaticals.

• Flexible working hours to fit productivity

Benefits & About the Business

• Comprehensive health benefits (medical, dental, vision)
• 401(k) with match and Employee Stock Purchase Plan
• Wellbeing programs, Headspace, Employee Assistance, time-off programs
• Disability, life, critical illness, hospital indemnity coverage
• Family benefits including bonding and family care leaves, adoption, surrogacy
• Health Savings, Dependent Care, and Commuter accounts
• Volunteer time and Employee Resource Groups

About the Business: LexisNexis Legal & Professional provides legal, regulatory, and business information and analytics to help customers increase productivity and decision-making.

#AIFluency

U.S. national base pay range: $118,300 - $219,800. Geographic differentials may apply. Eligible for annual incentive bonus.

We are committed to a fair and accessible hiring process. If you require accommodations, please contact us.