Manager Data Science

RELX•Raleigh, NC

About The Position

LexisNexis Legal & Professional is seeking a Manager of Data Science to lead a high-impact team building intelligent legal systems powered by large language models (LLMs) and retrieval-augmented generation (RAG). The role focuses on improving LLM-powered drafting and retrieval through advanced search, embeddings, reranking, evaluation, and production-grade machine-learning components. The manager will drive strategy, technical execution, and team growth to develop legal assistants capable of contextual document drafting and interacting with structured and unstructured data. The position includes defining a roadmap for LLMs and agentic AI in legal drafting, translating generative AI capabilities into customer value, and embedding AI-driven change across legal product platforms. The manager will architect systems combining foundation models with RAG pipelines and guide development of AI agents that reason across multiple steps, cite evidence, retrieve domain-specific content, and produce compliant outputs. They will mentor a multidisciplinary team, collaborate across functions, and establish best practices for evaluation, observability, and responsible generative AI use.

Requirements

At least 3 years of people-management experience with teams building LLM-based applications, especially in rigorous and traceable domains such as legal, finance, or compliance.
Hands-on experience delivering systems using LangChain, LLM agent frameworks, vector databases, and prompt orchestration pipelines.
Strong background deploying RAG systems for grounded and auditable responses.
Demonstrated success taking LLM-powered applications from prototype to production.
Proficiency with Python and LLM tooling, including LangChain, HuggingFace Transformers, OpenAI APIs, and prompt-tuning techniques.
Familiarity with vector databases such as Solr, Elasticsearch, Qdrant, and Weaviate, as well as knowledge graphs and hybrid retrieval architectures.
Working knowledge of containerization (Docker, Kubernetes), CI/CD, and model-serving tools (TorchServe, Triton, Ray Serve).
Cloud infrastructure experience on AWS, Azure, or GCP.
Six years of post-degree experience, with at least 3 years in a data science or applied AI leadership role focused on NLP/LLM systems.

Nice To Haves

Graduate degree in Computer Science, AI, Machine Learning, or equivalent experience.
Prior experience in legal tech, legal AI, or document-intensive domains.
Familiarity with ethical and legal considerations when deploying generative AI in professional settings.

Responsibilities

Define the roadmap for applying LLMs and agentic AI to real-world legal drafting.
Evangelize and embed AI-driven change across legal product platforms.
Translate evolving generative AI capabilities into tangible customer value in the legal domain.
Architect systems combining foundation models with RAG pipelines to draft contracts, memos, and pleadings grounded in enterprise knowledge.
Guide development of AI agents that perform multi-step reasoning, cite evidence, retrieve domain-specific content, and produce compliant outputs.
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.