LLM Data Analyst (Danish and English)

You will review written material and reasoning scenarios to help improve large language models. Your work will focus on clear answers, careful research, sound reasoning, and useful feedback.

• Read and summarize large bodies of content into smaller logical sections.
• Research information online and validate claims in written material.
• Answer questions about data interpretation, trends, logical reasoning, and basic arithmetic.
• Create scenarios and reasoning examples for language model training.
• Provide correct answers, explanations, constructive feedback, and detailed annotations.
• Review topics such as monthly sales distributions and rule-based delivery puzzles.

What it pays and takes

This is a remote, part-time contractor assignment for an independent contributor. The project may be extended based on performance and project needs.

• Pay: The role does not include a stated rate.
• Time: 20 or more hours per week.
• Location: Remote and open worldwide.
• Language: Professional fluency in Danish and English.
• Level: Entry level.
• Requirements: Strong analytical, research, critical-thinking, and logical-reasoning skills.
• Requirements: Clear written communication, detailed feedback skills, creative problem-solving, and the ability to work independently.
• Equipment: A reliable desktop or laptop and a good internet connection.
• Helpful background: Business analysis, research, copywriting, journalism, technical writing, editing, or translation.
• Helpful background: Study or experience in engineering, literature, journalism, communications, arts, statistics, or a related field.
• Helpful skills: Excel, Google Suite, data interpretation, and basic arithmetic.
• Education: A bachelor's degree is welcome, but relevant experience can replace formal education.

How it works

Apply on OpenTrain with your resume, then complete the application on the hiring site.

About AI training work

AI training is the human work behind systems that can understand and generate text. Contributors review examples, write answers, and give detailed feedback so models learn to summarize information, reason through problems, and communicate more clearly.