Sr. Manager Data Science - Gen AI & Content Systems

Salary: $118,300 - 219,800 per year Requirements:

• We strongly prefer an advanced degree in Data Science, Computer Science, Statistics, or a related discipline, or equivalent hands-on experience.
• We are also open to candidates with a bachelors degree in a relevant field and substantial applied experience in data science, machine learning, or AI.
• We typically look for 8+ years of relevant experience in data science, machine learning, or applied AI.
• We typically look for 4+ years of leadership experience, either direct or indirect team management.
• We value demonstrated impact, technical depth, and leadership, especially for candidates with non-traditional career paths.
• We need proven ability to lead through technical authority and organizational influence.
• We expect you to act as a change agent and embed strong practices into workflows and systems.
• We look for the ability to choose the right tools and technologies to solve business challenges.
• We need strong proficiency with Python and ML/LLM tooling such as Google ADK, LangChain, TensorFlow, PyTorch, and prompt tuning techniques.
• We value familiarity with vector databases, knowledge graphs, and hybrid retrieval architectures.
• We require strong experience working with structured and unstructured data at scale.
• We need the ability to design and implement data pipelines and preparation workflows.
• We expect experience integrating machine learning into complex, multi-stage processing systems.
• We look for working knowledge of containerization, CI/CD, RESTful API design, and model serving tools.
• We prefer cloud infrastructure experience with AWS, and also welcome Azure or Google Cloud Platform experience.
• We value familiarity with AI coding tools such as GitHub Copilot, Claude Code, and OpenAI Codex.
• Prior experience in legal tech, legal AI, or document-intensive environments is highly desirable.
• We prefer familiarity with ethical and legal considerations involved in deploying generative AI in professional settings.

• We set the vision and strategic priorities for Data Science and serve as a recognized expert in the function.
• We lead and develop a team of data scientists and ML engineers, shaping the teams culture and performance.
• We drive applied research with a clear route to production while balancing innovation with latency, cost, and reliability constraints.
• We build and scale evaluation science capabilities, including offline evaluation frameworks, automated benchmarking, and human-in-the-loop feedback systems.
• We champion rapid hands-on prototyping and iterative development.
• We collaborate with other Data Science teams to reuse components and patterns and reduce duplication and waste.
• We operate across multiple cross-functional teams, systems, and domains.
• We help define and execute the AI roadmap across the content lifecycle, including content collection and transformation, metadata extraction, enrichment and classification, agentic workflows, and downstream AI-powered product features.
• We design and deploy scalable production-grade AI systems, including LLM-driven document understanding and generation, RAG pipelines, agentic workflows, and hybrid ML plus rules-based systems.
• We lead by example by writing code, building demos, running experiments, and contributing directly to production models.
• We establish and scale best practices in model development, evaluation, monitoring, prompt experimentation, data preparation, feature engineering, and reusable platform capabilities.
• We partner closely with engineering, architecture, and product leaders to integrate AI into large-scale distributed systems and align technical solutions with business outcomes.
• We translate complex, ambiguous problems into clear plans and executable solutions, and guide teams through delivery.
• We present tradeoffs and alternative approaches when delivery constraints arise.
• We mentor and grow a multidisciplinary team of LLM-focused data scientists and ML engineers.
• We drive collaboration with legal subject matter experts, data engineers, product managers, and design partners.
• We establish best practices for evaluation, observability, and responsible generative AI usage.
• We oversee infrastructure that supports continuous delivery and monitoring of LLM systems in production.

• AI
• API
• AWS
• Azure
• CI/CD
• Claude Code
• Cloud
• Copilot
• GitHub
• Support
• LLM
• Machine Learning
• Model Serving
• PyTorch
• Python
• RAG
• TensorFlow
• Web

More:

We are LexisNexis Legal & Professional, part of RELX, serving customers in more than 150 countries with 11,800 employees worldwide and more than 2,000 technologists, data scientists, and experts focused on responsible AI and advanced technologies. We build legal intelligence solutions powered by large language models, RAG, agentic systems, and large-scale structured and unstructured content platforms to help legal professionals move faster and work with greater confidence. This is a U.S.-based remote opportunity for a Senior Manager of Data Science, and we offer flexible working hours, wellbeing initiatives, shared parental leave, study assistance, sabbaticals, and a broad benefits package that includes medical, dental, and vision coverage, retirement support, wellness tools, family benefits, and paid time for volunteering and employee resource groups. The role also includes a U.S. national base pay range of $118,300 to $219,800 and eligibility for an annual incentive bonus.

last updated 33 week of 2026