Senior Data Scientist – GenAI/LLM Production, Flexible Hours

RELX; Toronto; On-site; CAD 108,000 - 158,000; Full time

Benefits offered by this job

Shared parental leave

Study assistance

Sabbaticals

Flexible working hours

Job summary

LexisNexis Legal & Professional, part of RELX, seeks a Senior Data Scientist II in Toronto to advance generative AI, RAG, and agentic AI systems in production. You will design, refactor, test, deploy, and support robust Python applications with strong observability and secure handling of credentials.

The role emphasizes production readiness, cross-functional delivery, and ownership from design to deployment, with a focus on latency, cost, and reliability for AI-driven legal tech.

Qualifications

• Advanced Python proficiency demonstrated through production applications.
• Strong fundamentals and design principles for scalable systems.
• Experience transforming prototype into production-ready software.
• Production ownership including testing, monitoring and security.

Responsibilities

• Architect modular, agentic applications with clear interfaces.
• Refactor legacy Python code for readability and performance.
• Own production readiness and secure handling of credentials.
• Establish observability with logging, metrics, and tracing.
• Design data contracts between components and retrieval systems.
• Write unit, integration, and end-to-end tests including failure modes.
• Lead code reviews and mitigate architectural risks.
• Optimize latency, memory, and cost in production.

Skills

Python

LLM systems

Testing with pytest

Software design

Production ownership

Tools

OpenSearch

Solr

Monorepo

CI tooling

Job description

LexisNexis Legal & Professional, part of RELX, seeks a Senior Data Scientist II in Toronto to advance generative AI, RAG, and agentic AI systems in production. You will design, refactor, test, deploy, and support robust Python applications with strong observability and secure handling of credentials.

The role emphasizes production readiness, cross-functional delivery, and ownership from design to deployment, with a focus on latency, cost, and reliability for AI-driven legal tech.