Data Quality Analyst

Careerscape; New York (NY); Remote; USD 42,000 - 52,000; Full time

Job summary

Careerscape is seeking an entry-level AI Data Quality Associate to help annotate data and review for accuracy in AI workflows. You will evaluate examples against written criteria, identify errors, and clearly explain decisions.

The role suits individuals who enjoy detailed review, problem-solving, and learning how reliable data supports AI systems. As a remote team member, you will follow established guidelines, document decisions, escalate uncertain cases, and participate in calibration

Qualifications

• Strong reading comprehension, attention to detail, and written communication.
• Ability to apply a rubric consistently and distinguish evidence from assumptions.
• Willingness to learn annotation guidelines and incorporate feedback.
• Sound judgment when handling confidential or sensitive information.
• Ability to maintain accuracy during repetitive work and communicate remotely.

Responsibilities

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

Skills

Reading comprehension

Attention to detail

Written communication

Rubric application

Remote work communication

Judgement

Job description

Help improve the quality of data used in artificial intelligence workflows. This entry-level, remote AI Data Quality Associate role centers on data annotation, content review, accuracy checks, and consistent application of review guidelines.

You will evaluate examples against written criteria, identify errors, and explain your decisions clearly. This role is a fit for someone who enjoys detailed review work, thoughtful problem-solving, and learning how reliable data supports AI systems.

Key Responsibilities

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

Requirements

• Strong reading comprehension, attention to detail, and written communication.
• Ability to apply a rubric consistently and distinguish evidence from assumptions.
• Willingness to learn annotation guidelines and incorporate feedback.
• Sound judgment when handling confidential or sensitive information.
• Ability to maintain accuracy during repetitive work and communicate remotely.