Business Analyst (French Language)

You will create and evaluate text-based training material that helps large language models improve their reasoning, research, and analytical performance. The work involves detailed reading, research, problem solving, and feedback on model responses.

• Read, summarize, and divide large bodies of content into clear logical sections.
• Research topics online and validate claims in written material.
• Answer questions involving data interpretation, logical reasoning, lateral thinking, and basic arithmetic.
• Create scenarios and examples based on difficult reasoning problems.
• Provide correct answers, explanations, constructive feedback, and detailed annotations.
• Assess model outputs for accuracy, clarity, and logical soundness.

This is an entry-level, part-time contract role that requires careful analysis, clear writing, and independent work. The duties and qualifications should be reviewed before applying.

• Open to candidates worldwide.
• Work 20 or more hours per week.
• Professional fluency in French and English.
• Strong analytical, research, and English comprehension skills.
• Ability to reason through quantitative, logical, and lateral thinking problems.
• Clear written communication and professional collaboration skills.
• Ability to work independently in a remote setting.
• Reliable desktop or laptop and internet connection.
• Useful backgrounds include business analysis, research analysis, copywriting, journalism, technical writing, editing, or translation.
• Study or experience in engineering, literature, journalism, communications, arts, statistics, or a related field may be helpful.
• Familiarity with Excel and Google Suite supports the work.

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

AI training is the human work behind systems that learn from examples, including reviewing model answers, writing prompts, and preparing text for evaluation. Strong writing, research, language, and subject knowledge help people produce reliable examples and feedback for these systems.