Subject Matter Expert – Data & Statistical Chart Analysis (AI Benchmark)

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. Interpret complex data science and statistical visualizations—such as Sankey diagrams, heatmaps, calibration curves, residual plots, correlation matrices, and distribution plots—applying advanced professional judgement and terminology.
2. Design clear, objective, multi-step analytical tasks and questions based on challenging visualizations, emphasizing quantitative reasoning beyond surface-level chart reading.
3. Deliver precise, unambiguous answers with thorough, step-by-step written explanations, including explicit calculations, statistical inferences, or modeling logic as required.
4. Utilize exact data science and statistical language, ensuring accuracy in referencing units, scales, axes, legends, and annotations in all outputs.
5. Create tasks that require graphical reasoning, trend analysis, comparison, interpolation, and statistical inference, always avoiding ambiguous or subjective prompts.
6. Participate in remote collaboration, contributing via written and verbal channels, incorporating feedback, and maintaining consistent communication with project stakeholders.
7. Consistently produce objectively verifiable tasks and solutions to support the rigorous training and evaluation of advanced AI models.

Preferred Qualifications

1. Bachelor's degree or equivalent professional experience in Data Science, Statistics, Applied Mathematics, Computer Science, Operations Research, or a related quantitative field.
2. Minimum of two years’ professional, academic, or research background engaging with statistical models, data visualizations, or analytical reporting.
3. Advanced proficiency in interpreting axes, legends, units, scales, confidence intervals, and statistical annotations across diverse chart types.
4. Demonstrated ability to clearly articulate analytical processes and quantitative reasoning in high-quality written and verbal English.
5. Bilingual proficiency in English and, ideally, a second language relevant to your domain.
6. Experience with technical documentation, publication, assessment design, or structured analytical task development.
7. Background in producing data-annotation tasks, benchmark questions, technical reports, or related materials for data science, statistics, or AI-driven projects.