Patent Data Quality Engineer—AI Readiness

LexisNexis Legal & Professional; United Kingdom; Remote; GBP 50,000 - 80,000; Full time

Job summary

LexisNexis Intellectual Property, part of RELX, seeks a Patent Data Specialist (Enrichment Quality & AI Readiness) to work hands-on with patent data using SQL, Python and AI tools to improve data quality and readiness for AI applications.

You will collaborate with senior patent data experts to define correct standards, test data against them, and investigate root causes, with opportunities to become a recognized expert in a critical data foundation.

Qualifications

• Experience working with patent data or patent information in roles.
• Understanding of patent data structures: families, priority claims, kind codes, legal status, and assignees.
• Proficient in SQL or Python for data querying and analysis.
• Knowledge of AI tools for data analysis and enrichment.
• Clear written communication about data rules and edge cases.

Responsibilities

• Define and maintain quality standards for patent families, ownership, legal status, and coverage.
• Build versioned test sets and worked examples for automatic checks.
• Analyze data to identify quality problems and root causes, proposing fixes.
• Lead small quality-improvement projects end-to-end.
• Review data from new sources before it enters the platform and assess impact.
• Document data rules for automated tools and workflows.
• Present findings to colleagues and stakeholders.

Skills

SQL

Python

AI tools

Data analysis

Education

Bachelor's degree in a scientific/engineering/technical/information science or related subject

Tools

Patent databases

Job description

LexisNexis Intellectual Property, part of RELX, seeks a Patent Data Specialist (Enrichment Quality & AI Readiness) to work hands-on with patent data using SQL, Python and AI tools to improve data quality and readiness for AI applications.

You will collaborate with senior patent data experts to define correct standards, test data against them, and investigate root causes, with opportunities to become a recognized expert in a critical data foundation.