
Content Autocoding Specialist
1 week ago
**Job Description**:
As a Content Autocoding specialist, you will supervise and write rules on top of this automatic analysis in order to achieve the high levels of Precision and Recall that are necessary in our Categorization process. Additionally, you may use the same AI-powered text analytics tools to extract facts and events from Factiva and Dow Jones content to support multiple internal and external use cases.
You will report to the Manager, Autocoding, based in Singapore and you will be part of the Factiva Content’s Metadata team.
You Will:
- Develop and maintain document training sets for linguistics-based categorization tool.
- Test software releases as categorization tools are improved.
- Perform coding quality monitoring of publications, scoring documents and refining categorization rules to ensure the highest levels of precision and recall.
- Undertake research and analysis to improve the overall enrichment of Factiva content.
- Troubleshoot auto-categorization problems.
- Answer quality questions escalated internally or via Customer Service/Sales.
- Perform special ad-hoc projects as needed to support the needs of the business.
You Have:
- Proficiency in English and Chinese (ability to read both Chinese Traditional and Chinese Simplified scripts)
- College degree or library science, linguistics, research or journalism background.
- Understanding of Boolean search logic.
- Attention to detail.
- Research and analytical skills.
- General interest in current affairs.
Preferred:
- Understanding of Dow Jones Intelligent Identifiers.
- Experience with taxonomies and classification systems.
- Experience with auto-categorization products.
Dow Jones, Making Careers Newsworthy
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, protected veteran status, or disability status. EEO/AA/M/F/Disabled/Vets.
Business Area: PIB - DATA STRATEGY
Job Category: Data/Content Group
Union Status:
Req ID: 34501
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