Human Data Quality Analyst, AI Business

Highlights

• Ensure human data powering frontier AI labs captures the right signal.
• Investigate quality shifts and turn findings into automated validations.
• Design rubrics, gold sets and quality gates for new AI data programmes.

What they offer

• base salary
• equity
• benefits
• cash bonus or commission opportunity

Ideal candidate

Early-career analyst with 1-2 years working with real data who loves digging into ambiguity, spotting patterns, and turning evidence into clear, actionable stories for AI data quality.

Requirements

• 1 to 2 years of practical experience analysing real data in an analytical, quality, research or data-focused role
• Use SQL and Python to write queries and analysis, check results and explain reasoning
• Apply statistical concepts such as sampling, distributions and variability to judge meaningful patterns
• Turn evidence into clear account with concrete examples and practical recommendations for non-technical colleagues
• Assess detailed work carefully and consistently while looking for patterns across dataset, process or programme
• Test sensible approach, document reasoning and recognise when input needed when method is unclear
• Experience with reinforcement learning from human feedback (RLHF), preference data and evaluation benchmarks
• Experience creating clear data visualisations or dashboards to help people understand and act on findings