Patent Data Specialist (Enrichment Quality & AI Readiness)

Relx Plc; United Kingdom; Remote; GBP 45,000 - 75,000; Full time

Job summary

Relx PLC's patent data team seeks a Patent Data Specialist (Enrichment Quality & AI Readiness) to clean and validate patent data, using SQL, Python, and AI tools. You will work with senior experts to define governance and test sets, ensuring accurate ownership, families, and legal status across jurisdictions.

You will analyze data for quality issues, propose fixes, and help design checks to prevent recurrence, while documenting rules for consistent, automated application.

Qualifications

• Experience with patent data or patent information in a data role.
• Understanding of families, priority claims, kind codes, legal status and authorities.
• Hands-on data skills in SQL, Python, or similar tools.
• Methodical approach to data quality, spotting anomalies and root causes.
• Practical use of AI tools in data work beyond basic chat.
• Clear written communication to explain data rules and edge cases.

Responsibilities

• Define and maintain quality standards for patent families, ownership, legal status and coverage.
• Build and maintain versioned test sets and worked examples for automated evaluation.
• Analyse data to find quality problems, investigate root causes with engineering.
• Lead small quality-improvement projects end to end with supporting colleagues.
• Assess data quality from new sources and authorities before/after entering the platform.
• Review output of automated AI-assisted enrichment and feed learnings back.
• Document rules and decisions clearly for consistent application.
• Present findings to colleagues and stakeholders.

Skills

SQL

Python

Data analysis

AI tools

Education

Science/Engineering/Info Science degree

Job description

Patent Data Specialist (Enrichment Quality & AI Readiness)

Do you enjoy working hands-on with messy patent data, using SQL, Python and AI tools?

Do you revel in finding the root cause of an error, then making sure it never happens again?

Come join us and help build the world's most trusted patent data, ready for the AI that professionals worldwide rely on.

About the team

LexisNexis Intellectual Property, part of RELX, helps the world's innovators, IP professionals, law firms, and investors understand patents: their own, their competitors', and those of the companies they are assessing. Our products, including PatentSight+, IPlytics and TotalPatent One, and the patent data we deliver directly into customers' own systems, inform decisions on R&D investment, licensing, litigation, M&A and competitive strategy.

Every one of those decisions rests on the same foundation: patent data that is grouped, attributed, and kept up to date correctly. We are looking for someone who wants to help get that foundation right.

About the role

Patent data is hard for people and machines alike. One invention can be filed in dozens of countries under different numbers and rules; one company can hold patents under many names, subsidiaries, and spellings; and whether a patent is still alive depends on events spread across years and jurisdictions. Any data or AI system built on top is only as good as the answers to a few basic questions. Which filings belong to the same family? Who really owns a patent once subsidiaries, acquisitions and spelling variants are untangled? Is a patent still in force, and do we know this for every country we are interested in? A single wrongly grouped family or misattributed owner can quietly change how a customer sees a competitor.

In this role, you will work alongside senior patent data experts to define what correct looks like for these foundations, test our data against it, and track down why things go wrong. It is a rare chance to combine patent knowledge with hands-on data work, and to grow into a recognised expert in an area that underpins everything we do.

Key Responsibilities

• Work with our senior patent data experts to define and maintain governed quality standards and acceptance criteria for patent families, ownership, legal status, and coverage, including how to handle tricky edge cases.


• Build and maintain versioned test sets and worked examples, such as correctly grouped families or correctly resolved owners, that engineering teams build closed-loop evaluations on, so data quality is checked automatically and continuously.


• Analyse our data to find quality problems, investigate their root causes with engineering teams, recommend fixes, and help design checks so they do not recur.


• Lead smaller quality-improvement projects end to end, with support from senior colleagues.


• Assess the quality of data from new sources and patent authorities before and after it enters our platform.


• Review the output of automated and AI-assisted enrichment, such as ownership mapping, and feed what you learn back into the standards and evaluations.


• Document rules and decisions clearly so they can be applied consistently, by people and by automated tools, including agentic workflows.


• Help resolve data questions raised by product teams and customers, sometimes against tight timelines, and turn recurring ones into reusable guidance.


• Present findings to colleagues and stakeholders

Requirements

• Experience working with patent data or patent information, for example as a patent analyst, patent information specialist, searcher, or in a data role at a patent office, data provider, or IP firm.


• Understanding of how patent data is structured: families, priority claims, kind codes, legal status, assignees, and the differences between patent authorities.


• Hands-on data skills: you are comfortable querying and analysing data yourself, for example in SQL, Python, or similar tools.


• A methodical approach to data quality: spotting anomalies, finding root causes and checking that fixes work.


• Practical use of AI tools in your own work beyond basic chat, for example AI-assisted data analysis, coding assistants or automated extraction, and an understanding of where automated and AI-based enrichment can go wrong.


• Precision and care with detail, combined with the judgment to know which problems matter most.


• Clear written communication: you can explain a data rule or an edge case so others can apply it.

Experience and education

Typically, 2 or more years in patent information, patent analysis, or data roles involving patents or similarly complex data.

A degree in a scientific, engineering, technical, information science or related subject, or equivalent practical experience

It would be great if you also have.

• Experience with company ownership data, corporate hierarchies, or entity resolution


• Experience with non-English patent data, for example Chinese, Japanese or Korean


• Familiarity with data modelling, taxonomies, or classifica