- Experience
- Any
- Salary
- —
- Openings
- 1
- Posted
- 1 week ago
- Work mode
- Work from home
- Eligibility
- Applicants must currently reside in Australia, Canada, Ireland, New Zealand, or the United States. Applications outside these locations will be rejected.
- Resume
- Required to apply
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Job description
About the Role
This position is for a detail-focused Data Analyst responsible for reviewing, annotating, and organizing diverse multimodal datasets to facilitate advancement in artificial intelligence models. The datasets include text, images, spreadsheets, and complex structured documents. The role is fully remote, open to applicants residing in Australia, Canada, Ireland, New Zealand, or the United States.
Key Responsibilities
- Categorize and label a variety of datasets including text, images, and documents to support development of cutting-edge AI models.
- Evaluate AI-produced text and media to ensure it aligns with human intent and factual accuracy.
- Detect edge cases, ambiguities in labeling, and inconsistencies in data to enhance classification taxonomies.
- Maintain consistent daily throughput while ensuring strict adherence to quality assurance standards.
Candidate Requirements
- Exceptional attention to detail paired with robust analytical and comprehension skills.
- Background in UI/UX evaluation, editorial analysis, quality control, or preparing data for machine learning is advantageous.
- Fluency in English at native or professional proficiency level, both spoken and written.
- Reliable high-speed internet connection and access to a personal computer fulfilling system specifications.
- Must be physically located within the US or Canada; applications outside these regions will not be considered.
Equal Employment Opportunity
This organization values diversity and inclusivity, welcoming applicants from all backgrounds without regard to race, ethnicity, nationality, gender identity or expression, sexual orientation, age, religion, disability, or marital status. Employment decisions are based exclusively on qualifications, skills, and merit.