Jobs at LexisNexis

The Director of Data Sciences leads a team in strategic initiatives, drives machine learning and AI solutions, and manages resources to enhance data-driven decision making across the business unit.

Lead design, build, and operation of cloud-native container platforms on AWS (EKS/ECS/Fargate). Manage multi-tenant Kubernetes clusters, GitOps (Argo CD), Helm packaging, IaC (Terraform/CloudFormation), scripting (Go/Python/Bash), monitoring (Prometheus/Grafana/CloudWatch), incident response, cost optimization, and promote platform engineering and security best practices while mentoring engineers.

Generic entry-level associate role at LexisNexis focusing on supporting customers and enabling use of legal and business information solutions. Emphasis on equal-opportunity hiring and accessibility; specific responsibilities not provided.

Lead global AI-first transformation for legislative content: define strategy, prioritize AI-enabled content generation and workflows, deploy AI editorial tools, set standards, measure quality and performance, and build editorial AI capabilities across regions while partnering with product, engineering and editorial stakeholders.

Lead product planning and go-to-market strategy for the Law School market: translate customer insights and usage data into roadmap priorities, coordinate cross-functional launches, define requirements, drive adoption and tracking, and partner with Product, Marketing, Sales, and Operations to grow active users and downstream commercial outcomes.

Lead a team of Customer Success Consultants to drive trial enablement, onboarding, and adoption of drafting and DMS-integrated solutions for law firms. Build scalable programs, analyze usage data to identify expansion and risk, collaborate cross-functionally with Sales, Product, Marketing, and Data Science, engage executive stakeholders, and support renewals by improving customer health and demonstrating measurable value.

Lead finance business partnering for Editorial Operations, driving budgeting, forecasting, long-range planning, performance reporting, and investment analysis across a $100M+ global cost base. Advise senior leaders on AI‑enabled transformation, scenario modelling, productivity and cost-efficiency initiatives, and link financial and operational metrics to support strategic decisions.

Lead and manage data engineering teams to design, build, and maintain high-quality data pipelines. Oversee automation, performance scripting, data modeling, database optimization, and quality-control processes. Collaborate with product, engineering, and operations to deliver data-driven features and support SEC-related data needs and AI/LLM integrations.