AI Data QA Specialist (Remote, Project-Based)

prolificacademicltd; United States; Remote; USD 28,000 - 40,000; Part time

Job summary

Prolific Academic Ltd is seeking workers to review AI-generated records and perform high-volume data entry quality checks from a remote setting. You will assess accuracy, identify formatting issues, and provide structured, clean data samples to support model evaluation.

The role involves documenting errors, flagging inconsistencies, and contributing to data standards. A skills assessment is required; PayPal is used for task payments, and tasks are distributed flexibly.

Qualifications

• Professional experience in high-volume data entry, data processing, database administration, or records management.
• Strong attention to detail when checking large datasets for duplicates, inconsistencies, and formatting problems.
• Ability to process structured and unstructured information efficiently while maintaining accuracy.
• Understanding of data formats and validation rules, with the judgment to spot logical or factual errors in generated outputs.
• Written English skills sufficient to assess clarity and correctness.
• Access to a PayPal account for receiving task payments.

Responsibilities

• Check AI-generated records and data extractions for accuracy, completeness, and consistent formatting.
• Review datasets for categorization, labeling, and field-mapping errors, documenting issues against quality criteria.
• Create sample data-entry cases, including ambiguous or conflicting inputs, to evaluate model performance.
• Annotate and classify examples so systems can learn data structures and validation rules.
• Compare generated results with established data-entry standards and flag inconsistencies.

Skills

Data entry

Data processing

Database admin

Records management

Attention to detail

Quality assessment

English writing

Tools

Excel

Google Sheets

Airtable

SQL

Access

Job description

Prolific Academic Ltd is seeking workers to review AI-generated records and perform high-volume data entry quality checks from a remote setting. You will assess accuracy, identify formatting issues, and provide structured, clean data samples to support model evaluation.

The role involves documenting errors, flagging inconsistencies, and contributing to data standards. A skills assessment is required; PayPal is used for task payments, and tasks are distributed flexibly.