Remote AI Data QA & Labeling Specialist

prolificacademicltd; Stati Uniti; Remoto; USD 28.000 - 40.000; Part-time

Vantaggi offerti da questo lavoro

Remote work

Flexible scheduling

Descrizione del lavoro

Prolific Academic Ltd. is seeking a remote data quality reviewer to help evaluate AI-generated data entries and structured records. You will review, annotate, and classify samples to improve data structures and validation rules, ensuring accuracy and consistency across large datasets.

Applicants should have strong written English and experience with data formats, validation rules, and detecting errors. The role offers flexible scheduling and assignment-based payments, with compensation up to $25

Competenze

• Professional experience with high-volume data entry, data processing, or records administration.
• Strong attention to detail and ability to spot duplicates and formatting issues across large datasets.
• Efficiently processing structured and unstructured information without lowering quality.
• Familiarity with data formats, validation rules, and detecting logical or factual errors in AI-generated results.
• Written English skills adequate for evaluating clarity and correctness.

Mansioni

• Review generated entries, data extractions, and structured records for accuracy and format consistency.
• Annotate and classify samples to teach systems appropriate data structures and validation rules.
• Identify and flag dataset errors involving categories, labels, or field mappings using quality guidelines.
• Prepare realistic tests that challenge systems with untidy inputs, ambiguous fields, or conflicting records.
• Compare system outputs with established standards for professional data quality.

Conoscenze

Data entry

Data processing

Quality assurance

Attention to detail

Written English

Strumenti

Excel

Google Sheets

Airtable

SQL

Access

Descrizione del lavoro

Prolific Academic Ltd. is seeking a remote data quality reviewer to help evaluate AI-generated data entries and structured records. You will review, annotate, and classify samples to improve data structures and validation rules, ensuring accuracy and consistency across large datasets.

Applicants should have strong written English and experience with data formats, validation rules, and detecting errors. The role offers flexible scheduling and assignment-based payments, with compensation up to $25