AI Data Quality Associate (Remote, Entry-Level)

Careerscape; United States; Remote; USD 45,000 - 60,000; Full time

Job summary

Careerscape is seeking an AI Data Quality Associate for full-time remote work in the United States. The role focuses on data annotation, review, and ensuring accuracy within AI workflows. Entry-level position emphasizing learning and adherence to review guidelines.

Responsibilities include labeling data, checking for consistency, and escalating ambiguous cases while documenting decisions. Strong attention to detail and ability to work remotely are essential.

Qualifications

• Strong reading comprehension and attention to detail.
• Ability to apply a rubric consistently and distinguish evidence from assumptions.
• Comfort with spreadsheets, browser-based tools, and structured data.
• Willingness to learn annotation guidelines and incorporate feedback.
• Sound judgment handling confidential or sensitive information.
• Ability to maintain accuracy during repetitive work and communicate remotely.

Responsibilities

• Review and label text or other data using annotation guidelines.
• Check records for missing information, inconsistent labels, and duplicates.
• Evaluate AI-generated responses against quality criteria and reference materials.
• Record review decisions with clear notes for ambiguous cases.
• Escalate uncertain examples instead of guessing.
• Apply reviewer feedback and participate in calibration exercises.
• Track completed work and recurring issues following data-handling procedures.

Skills

Attention to detail

Strong reading comprehension

Written communication

Rubric-based evaluation

Evidence vs assumptions

Spreadsheet skills

Browser-based tools

Structured data

Willingness to learn

Discretion with confidential info

Remote work capability

Job description

Careerscape is seeking an AI Data Quality Associate for full-time remote work in the United States. The role focuses on data annotation, review, and ensuring accuracy within AI workflows. Entry-level position emphasizing learning and adherence to review guidelines.

Responsibilities include labeling data, checking for consistency, and escalating ambiguous cases while documenting decisions. Strong attention to detail and ability to work remotely are essential.