Quantitative Analyst AI Model Evaluator
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Bring real-world quantitative experience to remote AI model evaluation, with flexible scheduling and projects selected around your availability.
As an Experimentation Analyst and AI Trainer with DataAnnotation, you will test whether AI outputs withstand practical scrutiny. The work suits practitioners from statistics, finance, physics, biology, epidemiology, operations research, and related fields. You will contribute through careful analysis and written feedback.
Key Responsibilities:
- Validate AI-generated quantitative work against real-world standards
- Review data-driven insights for technical accuracy
- Create problems spanning forecasting and optimization
- Solve tasks involving experimental analysis and statistical inference
- Explain findings through well-documented analytical code
Requirements:
- At least two years of quantitative professional or research experience
- Some coding experience with end-to-end analytical workflows
- Practical statistical methods and predictive modeling experience
- Strong English fluency at native or bilingual level
- Quantitative bachelor's degree preferred; master's or PhD plus
Apply statistical judgment, scientific reasoning, and analytical coding to evaluate AI outputs for DataAnnotation's developing systems.