- Experience
- Any
- Salary
- USD 40 – USD 60 / hour
- Openings
- 1
- Posted
- 2 saat önce
- Work mode
- Work from home
- Eligibility
- Applications welcome from qualified candidates irrespective of background; selection based solely on technical expertise and skills.
- Resume
- Required to apply
Job description
Role Overview
We are seeking a dedicated Human Data Manager to join our client's team on a full-time remote basis. This role involves managing the collection, validation, and oversight of human-annotated datasets ensuring their precision and applicability for AI and other downstream technologies.
Key Responsibilities
- Continuously maintain and refresh human-annotated datasets employed in AI model training and assessment.
- Conduct thorough reviews and validations of data labels to guarantee uniformity and high quality across datasets.
- Collaborate closely with diverse teams to define data necessities and resolve annotation issues.
- Document the methodologies used for data gathering, the labeling standards, and quality control measures.
- Oversee the performance of data pipelines and introduce enhancements to boost operational efficiency.
Required Skills and Qualifications
- Prior experience in data annotation, validation, or quality assurance workflows.
- Familiarity with data labeling applications such as Label Studio or Prodigy is preferred.
- Proficiency with spreadsheets, database systems, or data management platforms.
- Meticulous attention to detail and the capability to adhere to structured guidelines when handling data tasks.
- Effective written communication skills for creating thorough process and guideline documentation.
Additional Information
This opportunity allows you to contribute to a top-tier company in the Data Infrastructure and Analytics sector, improving AI training datasets that impact multiple applications. The role supports scalable solutions to enhance model efficacy.
Equal Opportunity Employer Statement
Hiring decisions are based on skills and expertise without regard to personal background or prior employment. Candidates are evaluated purely on their technical qualifications and capabilities.