Database Administrator - Graduates - AI Training - Madrid, Spain

Prolific; Madrid; Híbrido; EUR 30.000 - 45.000; Jornada completa

Descripción de la vacante

Prolific, based in Madrid, seeks a Database Administrator for AI training. The role involves reviewing AI-generated data and executing data entry tasks with high accuracy. Candidates should have strong data literacy and communication skills.

With flexible work hours and support for remote work, successful candidates will leverage various data tools like Excel and SQL. Prolific offers a dynamic environment to maintain data quality for AI systems, with emphasis on accuracy and attention to detail.

Formación

• Years of experience in high-volume data entry, data processing, database management, or records administration.
• Proven track record of maintaining high accuracy rates across large datasets.
• High typing speed and the ability to process structured and unstructured data quickly.
• Familiarity with data formats and validation rules.
• Solid written English skills.
• Multilingual capabilities are a significant plus.
• A PayPal account to receive payment.

Responsabilidades

• Review AI-generated data for accuracy and formatting consistency.
• Create realistic data entry scenarios to test AI handling of inputs.
• Review AI-produced data for errors in categorization and flag issues.
• Tag and classify data samples for AI models.
• Compare AI outputs against data entry standards.

Descripción del empleo

Database Administrator - Graduates - AI Training

About Prolific

Prolific is not just another player in the AI space – we are building the biggest pool of quality human data in the world. Over 35,000 AI developers, researchers, and organizations use Prolific to gather data from paid study participants with a wide variety of experiences, knowledge, and skills.

Compensation & Work Hours

Researchers pay up to $25 per hour for tasks that require approximately one hour of uninterrupted work, with many tasks shorter. Flexible hours and ability to work from home.

What you’ll bring

• Professional Experience: years of experience in high-volume data entry, data processing, database management, or records administration.
• Accuracy & Attention to Detail: a proven track record of maintaining high accuracy rates across large datasets, with a sharp eye for inconsistencies, duplicates, and formatting errors.
• Speed & Efficiency: high typing speed and the ability to process structured and unstructured data quickly without sacrificing quality.
• Data Literacy: familiarity with data formats, validation rules, and the ability to identify when AI-generated outputs contain logical or factual errors.
• Communication Skills: solid written English skills sufficient to assess clarity and correctness in AI-generated text.
• Language Proficiency: multilingual capabilities are a significant plus, especially for evaluating data quality across localized datasets.
• A PayPal account to receive payment from our clients.

What you’ll be doing in the role

• Evaluate AI Data Outputs: review AI-generated data entries, extractions, and structured records for accuracy, completeness, and formatting consistency.
• Simulate Data Entry Tasks: create realistic data entry scenarios and edge cases to test how AI handles messy inputs, ambiguous fields, or conflicting records.
• Audit AI-Generated Datasets: review AI-produced data for errors in categorisation, labelling, or field mapping, and flag issues against standard data quality rubrics.
• Annotation & Labelling: tag and classify data samples to help AI models learn correct data structures, formats, and validation rules.
• Quality Assurance: compare AI outputs against established data entry standards to ensure they meet professional accuracy and consistency benchmarks.

Key Technologies

• Data Tools: proficiency with Microsoft Excel, Google Sheets, or database platforms such as Airtable, SQL, or Access.
• Data Management Systems: experience with CRM platforms, ERP systems, or document management tools.
• Documentation: familiarity with Confluence, Notion, or similar platforms for referencing data standards and internal guidelines.

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