Data Science-AI Trainer

Job Description

Data Science AI Trainer Overview

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• The Data Science AI Trainer role involves evaluating AI models on real-world data science tasks.
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• Contribute to improving AI systems by designing realistic, challenging tasks based on professional experience.
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• Work remotely with flexible scheduling, engaging in project-based AI training activities.
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• Collaborate with frontier AI labs to enhance human-aligned AI capabilities.
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• Utilize your expertise to assess AI outputs against professional standards.
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• Gain access to advanced AI tools like Claude and ChatGPT for project work.
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• Participate in structured, self-directed tasks requiring clear written reasoning and technical depth.
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• Engage in an innovative role that combines data science expertise with AI evaluation.
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• Contribute to the development of trustworthy AI systems through professional collaboration.
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Data Science AI Trainer Key Responsibilities & Duties

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• Design and execute realistic data science tasks based on professional workflows.
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• Evaluate AI model outputs against professional standards and document findings.
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• Develop grading rubrics and tests to assess deliverables for accuracy and completeness.
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• Identify and flag concrete failures in AI outputs with evidence and reasoning.
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• Contribute to analytics, machine learning, and experimentation tasks.
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• Review and refine tasks created by other experts to ensure quality and relevance.
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• Craft scenarios that test AI systems' ability to perform professional-level work.
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• Provide detailed feedback and revisions to improve AI task outcomes.
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• Collaborate with a team of professionals to advance AI training methodologies.
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Data Science AI Trainer Job Requirements

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• Bachelor’s degree in a quantitative field, with practical applied work experience.
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• Minimum of 2 years professional experience in applied data science or related fields.
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• Proficiency in Python and SQL for writing and debugging analysis code.
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• Depth in analytics, machine learning, experimentation, or data engineering.
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• Ability to independently own multi-step analyses from raw data to actionable insights.
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• Strong written communication skills to articulate reasoning and evaluate results.
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• Comfort with ambiguity and attention to detail in professional tasks.
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• Familiarity with AI tools and judgment to assess their outputs critically.
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• Availability for at least 10 hours per week in a remote setting.
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