数据分析师（AI 评估）
Data Analyst (AI Evaluation)
薪资：每小时30-60美元（美元）。
职位名称：数据分析师（AI评估）
职位类型：承包商
地点：远程，美国本地
micro1 正在招募数据分析师，为客户的数据显示质量项目贡献他们的知识和专长。在这个职位中，您将运用专业知识帮助训练下一代人工智能系统。您的工作将影响模型如何学习、推理和表现，通过高质量的真实输入。无需人工智能相关经验——您的领域知识才是关键。
工作范围
1. 审查数据集和详细任务输出，确保准确性、完整性和符合指南。
2. 识别并标记不一致之处、错误以及与提供指令不符的输出。
3. 在大规模数据集中一致地应用结构化评分标准和评估准则。
4. 在指南不明确的模糊情况下，运用合理判断并记录理由。
5. 对于模式性或重复性的数据问题进行上报以进一步分析，而不是单独处理。
6. 提供清晰、可操作的书面和口头反馈，准确指出问题并提出解决路径。
7. 在处理大量重复数据审查任务时保持细致入微的注意力。
优先资格
1. 3–5年以上数据审查、数据质量、质量保证或分析相关工作经验。
2. 在基于明确标准审查、验证和批判数据或交付物方面有实际经验。
3. 能够精确遵循详细书面说明并应用复杂评估评分标准。
4. 在不确定情况下表现出色，包括在指南不完整时做出合理决策。
5. 在重复或高数量的工作中具备出色的细节关注和错误识别能力。
6. 具备良好的书面和口头沟通能力，用于记录发现和提供反馈。
7. 基础的电子表格技能（排序、筛选、简单公式）；熟悉SQL或实际数据查询者优先。
8. 具有数据标注、标记或基于评分标准的评估经验者更具优势。
查看英文原文
**Pay:** $30-$60 per hour (USD).
Role Title: Data Analyst (AI Evaluation)
Role Type: Contractor
Location: Remote, US-based.
micro1 is engaging Data Analysts to contribute their knowledge and expertise to a customer’s data quality project. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.
Scope of Work
1. Review datasets and detailed task outputs for accuracy, completeness, and adherence to guidelines.
2. Identify and flag inconsistencies, errors, and outputs that deviate from provided instructions.
3. Apply structured rubrics and evaluation criteria consistently across large data sets.
4. Exercise sound judgment and document rationale in ambiguous scenarios where guidelines are unclear.
5. Escalate patterns or recurring data issues for further analysis rather than addressing them individually.
6. Provide clear, actionable written and verbal feedback pinpointing issues and suggesting resolution paths.
7. Maintain meticulous attention to detail while working through high volumes of repetitive data review assignments.
Preferred Qualifications
1. 3–5+ years of experience in data review, data quality, quality assurance, or analytical roles.
2. Proven expertise in reviewing, validating, and critiquing data or deliverables based on explicit criteria.
3. Exceptional ability to follow detailed written instructions and apply complex evaluation rubrics precisely.
4. Demonstrated comfort with ambiguity, including making justifiable decisions when guidelines are incomplete.
5. Advanced attention to detail and error-spotting capabilities across repetitive or high-volume work.
6. Strong written and verbal communication skills for documenting findings and providing feedback.
7. Baseline fluency with spreadsheets (sorting, filtering, simple formulas); SQL or hands-on data querying is a plus.
8. Experience with data annotation, labeling, or rubric-based evaluation is advantageous.