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[Remote] Data Labeling Specialist (Consultancy)
Note: The job is a remote job and is open to candidates in USA. Rhombus Power Inc. delivers AI-powered predictive intelligence for defense and national security organizations. The Data Labeling Specialist will verify and improve the quality of event data for predictive intelligence systems by reviewing event records and ensuring accuracy in classifications and tagging.
Responsibilities
- Review event records against original news sources to verify accuracy of event type, actors involved, location, and date
- Identify and flag coding errors, misattributions, or inconsistencies in event data
- Apply sound judgment on ambiguous cases; document reasoning to maintain validation consistency
- Proactively communicate with project leadership on progress, challenges, and workflow improvements, including quality assurance
- Help refine validation standards and contribute to process improvements where possible
- Develop deeper expertise in event data structures and gain familiarity with how validated datasets improve machine learning model performance
- Maintain and uphold data security standards while working in a fully remote environment
Skills
- An undergraduate degree, completed or in progress
- Strong knowledge of international affairs, geopolitics, or current events — regional expertise (South Asia, East Asia, Middle East, etc.) is a plus
- Excellent English reading comprehension; additional language proficiency is highly valued
- Strong command of Microsoft Suite and Google tools such as Excel, Word, Sheets, etc., with excellent file management and organizational skills
- Detail-oriented with experience reviewing data for errors or inconsistencies and making corrections to maintain quality and accuracy
- Proven analytical and logical reasoning skills — able to manage multiple datasets and tasks with precision and consistency
- Self-starter with a bias for action, strong attention to detail, and ability to maintain accuracy and productivity under tight deadlines in a fully remote, flexible setting
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