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Sr. Manager Data Science - Gen AI and Content SystemsLexisNexis Risk Solutions • Raleigh, North Carolina, United States
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Sr. Manager Data Science - Gen AI and Content Systems

LexisNexis Risk Solutions
  • US
    Raleigh, North Carolina, United States
  • US
    Raleigh, North Carolina, United States
Postuler Maintenant

À propos

Please note that 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, then 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 worldwide, and is part of RELX (www.relx.com). We are a global provider of information‑based analytics and decision tools for professional and business customers. We have been a long‑time leader in deploying AI and advanced technologies to the legal market, improving productivity, and transforming the overall business and practice of law. We develop 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. Our team employs over 2,000 technologists, data scientists, and experts to develop, test, and validate solutions in line with RELX Responsible AI Principles. LexisNexis Data Sciences
We are redefining legal intelligence through advanced AI. Our teams harness the power of large language models (LLMs), retrieval-augmented generation (RAG), agentic systems, and large‑scale structured and unstructured 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. Our applied research opportunity balances innovation with practical constraints (e.g., latency, cost, reliability) and requires a strong ability to quickly iterate on prototypes, communicate trade‑offs, and rapidly deploy to production environments. This role is central to our transformation toward an intelligent, agent‑enabled content platform capable of grounded reasoning, 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 for the group. Drive applied research with a clear path to production, explicitly 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 rigorously measure model quality and business impact. Champion hands‑on rapid prototyping and iteration. Collaborate with other Data Science teams to maximize re‑use of components and patterns, eliminating waste, duplication, and unnecessary customization. Operate with broad scope, coordinating across multiple cross‑functional teams, systems, and domains. Technical & Product Leadership
Collaborate closely with other Data Science teams to define and execute the AI roadmap across the content lifecycle, maximizing reuse in areas including content collection (e.g., web scraping) and transformation, metadata extraction, enrichment, and classification, and agentic workflows that turn real‑world events and legal content into legal intelligence. Design and deploy scalable, production‑grade AI systems, including LLM‑powered document understanding and generation, agentic workflows balancing agent autonomy and efficiency with required structure and accuracy, retrieval‑augmented generation (RAG) pipelines, and hybrid ML + rules‑based systems for structured content. Lead through execution and by example: actively write code, not just delegate; build and demo working prototypes; directly contribute to experiments and production models. Establish and scale best practices in Data Science, including model development, evaluation, and monitoring; prompt engineering and experimentation frameworks; data preparation and feature engineering standards; reusable components and platform capabilities. Partner closely with engineering, architecture, and product leaders to integrate AI into large‑scale distributed systems, ensure performance, scalability, and reliability, align technical solutions with business outcomes, translate complex ambiguous problems into clear project plans and executable solutions, and lead teams through delivery. Present trade‑offs, alternative approaches, and options when faced with 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 development of infrastructure to support continuous delivery and monitoring of LLM systems in production environments. Core Qualifications
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 in a relevant field with significant applied experience in data science, machine learning, or AI. 8+ years of relevant experience in data science, machine learning, or applied AI. 4+ years of leadership experience (direct or indirect team management). Demonstrated impact, technical depth, and leadership over strict credential requirements. Ability to lead through both technical expertise and organizational influence. Strong strategic vision and ability to embed best practices into workflows and systems. Experience defining tools and technologies to solve business problems. Technical Proficiency
Proficient with Python and ML/LLM tooling such as LangChain, TensorFlow, PyTorch, and prompt tuning techniques. Familiarity with vector databases, knowledge graphs, and hybrid retrieval architecture. Strong experience working with structured and unstructured data at scale. Ability to design and implement data pipelines and preparation workflows. 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. Knowledge of AI coding tools such as GitHub Copilot, Claude Code, and OpenAI Codex. Preferred Background
Graduate degree in Computer Science, AI, or Machine Learning. 8+ years of post‑degree experience, with 4+ years in a data science or applied AI leadership role focusing on NLP/LLM systems. Prior experience in legal tech, legal AI, or document‑intensive domains highly desirable. Familiarity with ethical/legal considerations in deploying generative AI in professional settings. Benefits
Health Benefits:
Comprehensive multi‑carrier program for medical, dental, and vision benefits. Retirement Benefits:
401(k) with match and an Employee Share Purchase Plan. Well‑being:
Wellness platform with incentives, Headspace app subscription, Employee Assistance and Time‑off Programs. Insurance:
Short‑ and Long‑Term Disability, Life and Accidental Death Insurance, Critical Illness, and Hospital Indemnity. Family Benefits:
Family care leaves, adoption, and surrogacy benefits. Accounts:
Health Savings, Health Care, Dependent Care, and Commuter Spending Accounts. Paid Leave:
Up to two days of paid leave each to participate in Employee Resource Groups and volunteer with your charity of choice. Salary
U.S. National Base Pay Range: $118,300 – $219,800. Geographic differentials may apply in some locations to better reflect local market rates. This job is eligible for an annual incentive bonus. Equal Employment Opportunity 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. USA Job Seekers: EEO Know Your Rights.
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  • Raleigh, North Carolina, United States

Compétences linguistiques

  • English
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