Sr. Manager Data Science - Gen AI & Content Sys.

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

• We prefer an advanced degree such as a Masters or PhD in Data Science, Computer Science, Statistics, or a related discipline, or equivalent hands-on experience.
• A bachelors degree in a relevant field plus substantial practical experience in data science, machine learning, or AI is acceptable.
• 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, including for candidates with non-traditional career paths.
• We need strong technical fluency with Python and LLM/ML tooling such as Google ADK, LangChain, TensorFlow, PyTorch, and prompt tuning methods.
• We look for 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 data preparation workflows.
• Experience integrating machine learning into complex, multi-stage processing systems is important.
• Working knowledge of containerization, CI/CD, RESTful API design, and model serving tools is expected.
• Cloud infrastructure experience with AWS is preferred, though Azure or Google Cloud Platform is also relevant.
• Familiarity with AI coding tools such as GitHub Copilot, Claude Code, or OpenAI Codex is helpful.
• A graduate degree in Computer Science, AI, Machine Learning, or equivalent experience is preferred.
• Experience in legal tech, legal AI, or document-heavy domains is highly desirable.
• Familiarity with ethical and legal considerations for deploying generative AI in professional environments is valued.

• We set the strategic vision and priorities for Data Science across our content ecosystem.
• We lead, mentor, and develop a team of data scientists and ML engineers while shaping the team culture.
• We drive applied research with a clear path to production, balancing innovation with latency, cost, and reliability constraints.
• We build and scale evaluation science, including offline evaluation frameworks, automated benchmarking, and human-in-the-loop feedback systems.
• We champion rapid prototyping, hands-on experimentation, and frequent iteration.
• We collaborate with other Data Science teams to reuse components and patterns and reduce duplication.
• We coordinate across multiple cross-functional teams, systems, and domains.
• We help define and execute the AI roadmap across the content lifecycle.
• We work on content collection and transformation, metadata extraction, enrichment, classification, and agentic workflows that convert real-world events and legal content into intelligence.
• We design and deploy scalable production-grade AI systems, including LLM-based document understanding and generation, RAG pipelines, hybrid ML and rules-based systems, and agentic workflows.
• We write code, build and demo prototypes, and contribute directly to experiments and production models.
• We establish best practices for model development, evaluation, monitoring, prompt engineering, experimentation, data preparation, feature engineering, and reusable platform components.
• We partner with engineering, architecture, and product leaders to integrate AI into large distributed systems and align technical solutions with business outcomes.
• We translate ambiguous challenges into clear plans and executable solutions, and guide teams through delivery.
• We present tradeoffs and alternative approaches when delivery constraints require practical decisions.
• We mentor and grow a multidisciplinary team focused on LLMs and ML engineering.
• We collaborate closely with legal subject matter experts, data engineers, product managers, and design partners.
• We establish evaluation, observability, and responsible AI practices.
• We oversee infrastructure that supports continuous delivery and production monitoring of LLM systems.

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

More:

We are LexisNexis Legal & Professional, part of RELX, serving customers in more than 150 countries with a global team of more than 11,800 employees. We are a long-standing leader in applying AI and advanced technology to the legal market, building ethical generative AI solutions that improve productivity and transform how legal and business information becomes actionable intelligence. Our Data Sciences team works with large language models, retrieval-augmented generation, agentic systems, and large-scale structured and unstructured content systems to power an intelligent content platform. This is a US-based remote opportunity with flexible hours and a strong focus on work/life balance. We offer comprehensive benefits including medical, dental, and vision coverage, a 401(k) with match, an employee share purchase plan, wellness resources, family benefits, spending accounts, disability and insurance coverage, and paid volunteer time. The role also includes an annual incentive bonus and a national base pay range of $118,300 to $219,800, with geographic adjustments where applicable.

last updated 37 week of 2026