Senior Manager Data Science

** 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, serving customers in over 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 is a leader in deploying AI and advanced technologies to improve productivity and transform the legal market. We prioritize using the best models from today's top creators for each legal use case.

About LexisNexis Data Sciences:

At LexisNexis, we're redefining legal intelligence through advanced AI. Our teams harness the power of large language models (LLMs), retrieval-augmented generation (RAG), and agentic systems to build tools that analyze, draft, and reason with legal text. Join us in building AI systems that help legal professionals move faster, think deeper, and operate with confidence.

Role Overview:

We are seeking a Senior Manager of Data Science to lead a high-impact team focused on building intelligent systems powered by LLMs and RAG architectures. This role centers on delivering AI agents that generate legal documents, interpret contracts, and autonomously execute multi-step tasks across complex legal workflows.

You’ll drive the strategy, technical execution, and team growth necessary to build next-generation legal assistants—capable of grounded reasoning, contextual document drafting, and interaction with structured and unstructured data sources.

Key Responsibilities:

Vision & Strategy:

• Define the roadmap for applying LLMs and agentic AI to real-world legal drafting, summarization, and task automation challenges.

• Evangelize and embed AI-driven change across legal product platforms.

• Translate evolving generative AI capabilities into tangible customer value within the legal domain.

Technical & Product Leadership:

• Architect systems that combine foundation models with RAG pipelines to draft contracts, memos, and pleadings grounded in enterprise knowledge.

• Guide the development of AI agents that perform multi-step reasoning, cite evidence, retrieve domain-specific content, and produce compliant outputs.

• Lead evaluation of model performance for generation, summarization, classification, and dialogue-based workflows with legal constraints in mind.

• Build scalable prompt engineering frameworks and manage fine-tuning or adaptation of models to legal datasets.

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:

Experience

• Previous people management experience (3+ years) of teams building LLM-based applications, especially in domains requiring rigor and traceability like legal, finance, or compliance.

• Hands-on experience delivering systems using LangChain, LLM agent frameworks, vector databases, and prompt orchestration pipelines.

• Strong background in deploying retrieval-augmented generation (RAG) systems for grounded and auditable responses.

• Demonstrated success in taking LLM-powered applications from prototype to production.

Technical Proficiency

• Proficient with Python and LLM tooling: LangChain, HuggingFace Transformers, OpenAI APIs, and prompt tuning techniques.

• Familiarity with vector databases (e.g., Solr, Elasticsearch, Qdrant, Weaviate), 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.

Preferred Background

• Graduate degree in Computer Science, AI, Machine Learning, or equivalent experience.

• 10 years of post-degree experience, with 4+ ye