LLM Data Analyst (Swedish)

You will help improve large language models by working with written content and training examples in English and Swedish. The work combines research, analytical question answering, reasoning, summarization, and detailed feedback on model responses.

• Read and summarize large documents by breaking them into clear, logical sections.
• Research information online and check whether claims in source material are accurate.
• Answer analytical questions and create scenarios that test reasoning, data interpretation, and basic arithmetic.
• Solve logic puzzles and explain your answers clearly.
• Review model outputs, give constructive feedback, and create detailed annotations.
• Work through examples such as comparing sales growth across locations or reasoning about rule-based delivery schedules.

The role is an entry-level, part-time contractor position. The job details do not list a pay rate.

• Time commitment: At least 20 hours per week.
• Location: Worldwide and remote.
• Languages: Strong English and Swedish capability is required.
• You need strong analytical, research, logical reasoning, and English comprehension skills.
• You must explain conclusions clearly, provide precise feedback, and think creatively about unfamiliar questions.
• Strong written and verbal communication and the ability to work independently are required.
• You need a reliable desktop or laptop computer and internet connection.
• Helpful experience includes business analysis, research, copywriting, journalism, technical writing, editing, or translation.
• Experience in engineering, literature, journalism, communications, arts, statistics, or a related field is welcome. Relevant experience may substitute for a bachelor's degree.
• Familiarity with Excel, Google Suite, data interpretation, and basic arithmetic is helpful.

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

AI training is the human work behind systems that learn from examples, including writing and rating answers, checking information, and reviewing model behavior. People with strong language, research, and analytical skills help make these systems more accurate and useful.