LexisNexis · Germany
Skills: Python, SQL
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(https://himalayas.app/companies/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 wr …truncated… himala…
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