Process drug-patent relationship analysis and classify patents into core, recommended, low-confidence review, or excluded.
Review patent abstracts, claims, descriptions, patent families, applicants, and public information.
Judge relationships between patents and drugs, structures, targets, indications, or mechanisms.
Add evidence snippets, sources, relationship types, confidence levels, and review reasons for each relationship.
Help define patent relationship schemas, recommendation tiers, exclusion rules, and quality standards.
Partner with the AI Native Data Engineer to convert patent judgment into prompts, QA rules, and error sample libraries.
2+ years of experience in patent data, drug patents, life sciences intelligence, pharmaceutical data, or IP content analysis.
Able to read English patent materials, including titles, abstracts, claims, patent families, applicants, and drug-related evidence.
Background in pharmaceuticals, chemistry, biology, patent information, or life sciences intelligence preferred.
Patent attorney qualification is not required.
Strong ability to document evidence, uncertainty, and reasoning.
Comfortable using AI tools to improve repeatability and throughput.
Chinese-English collaboration ability preferred.
