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LexisNexis Legal & Professional

Legal, government, and business intelligence platform

Patent Data Specialist - Enrichment Quality & AI Readiness

Data ManagementPosted on Nov 6
Full-timeRemote in UKNo salary listedRemote

About the Job

Requirements

  • Experience working with patent data or patent information, such as as a patent analyst, patent information specialist, searcher, or in a data role at a patent office, data provider, or intellectual property firm.
  • Understanding of patent data structures, including families, priority claims, kind codes, legal status, assignees, and differences between patent authorities.
  • Ability to query and analyze data hands-on using SQL, Python, or similar tools.
  • A methodical approach to data quality, including spotting anomalies, finding root causes, and checking that fixes work.
  • Practical use of AI tools beyond basic chat, such as AI-assisted data analysis, coding assistants, or automated extraction, and understanding of failure modes in automated and AI-based enrichment.
  • Precision and attention to detail, with judgment to prioritize problems.
  • Clear written communication and ability to explain data rules and edge cases so others can apply them.
  • Typically, at least 2 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.

Responsibilities

  • Work with senior patent data experts to define and maintain governed quality standards and acceptance criteria for patent families, ownership, legal status, and coverage, including handling difficult edge cases.
  • Build and maintain versioned test sets and worked examples, such as correctly grouped families or correctly resolved owners, for engineering teams to use in closed-loop evaluations and continuous automated data-quality checks.
  • Analyze data to identify quality problems, investigate root causes with engineering teams, recommend fixes, and help design checks to prevent recurrence.
  • 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 the platform.
  • Review automated and AI-assisted enrichment outputs, such as ownership mapping, and feed findings back into standards and evaluations.
  • Document rules and decisions clearly so people and automated tools, including agentic workflows, can apply them consistently.
  • Help resolve data questions raised by product teams and customers, sometimes against tight timelines, and turn recurring questions into reusable guidance.
  • Present findings to colleagues and stakeholders.

Desired Qualifications

  • Experience with company ownership data, corporate hierarchies, or entity resolution.
  • Experience with non-English patent data, such as Chinese, Japanese, or Korean.
  • Familiarity with data modelling, taxonomies, or classification systems.
  • Experience with data quality tooling or automated testing of data.

About the Company

LexisNexis Legal & Professional

Legal, government, and business intelligence platform

LexisNexis Legal & Professional provides legal, government, business, and high-tech information through subscription-based access to a vast repository of licensed news publications and corporate data. Its offerings, such as Nexis AI, enable advanced research, intelligence gathering, and automatic document summarization for professionals in law firms, corporations, government agencies, and academic institutions. The platform works by delivering curated information and insights from millions of companies and publications via a search and analysis interface, helping users find accurate information quickly. The company differentiates itself with a long history of service, a broad, licensed data library across multiple sectors, and AI-powered tools that streamline research and decision-making. Its goal is to help clients make informed decisions, achieve a competitive advantage, and boost efficiency by providing trusted information and tailored analytics.

Company size
5,001-10,000
Company stage
Growth Equity (Non-Venture Capital)
Total funding
$30M
Headquarters
New York City, New York
Founded
1973

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