Data Analyst; AI Evaluation

Required Skills

• Data Analysis
• Data Review
• Attention to detail
• Handling ambiguity
• Error spotting
• About micro1
• micro1 is the leading AI data lab for training frontier models and evaluating AI agents. Experts contribute their diverse subject matter knowledge across domains such as finance, healthcare, STEM engineering, and more. micro1 transforms that real-world expertise into high-quality training data, evaluations, and feedback loops that improve how AI systems learn, reason, and perform.

Our platform identifies and vets top talent through an AI recruiter, enabling high-quality expert contributions  aim to enable 1 billion people to do meaningful work by applying their expertise to AI. As our global expert network grows, micro1 is building the human intelligence layer for frontier AI.

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.

• Review datasets and detailed task outputs for accuracy, completeness, and adherence to guidelines.
• Identify and flag inconsistencies, errors, and outputs that deviate from provided instructions.
• Apply structured rubrics and evaluation criteria consistently across large data sets.
• Exercise sound judgment and document rationale in ambiguous scenarios where guidelines are unclear.
• Escalate patterns or recurring data issues for further analysis rather than addressing them individually.
• Provide clear, actionable written and verbal feedback pinpointing issues and suggesting resolution paths.
• Maintain meticulous attention to detail while working through high volumes of repetitive data review assignments.

• 3–5+ years of experience in data review, data quality, quality assurance, or analytical roles.
• Proven expertise in reviewing, validating, and critiquing data or deliverables based on explicit criteria.
• Exceptional ability to follow detailed written instructions and apply complex evaluation rubrics precisely.
• Demonstrated comfort with ambiguity, including making justifiable decisions when guidelines are incomplete.
• Advanced attention to detail and error-spotting capabilities across repetitive or high-volume work.
• Strong written and verbal communication skills for documenting findings and providing feedback.
• Baseline fluency with spreadsheets (sorting, filtering, simple formulas); SQL or hands‑on data querying is a plus.
• Experience with data annotation, labeling, or rubric-based evaluation is advantageous.