Bring real-world quantitative experience to remote AI model evaluation, with adaptable 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.

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📌 Quantitative Analyst AI Model Evaluator (Quebec City)
🏢 DataAnnotation
📍 Quebec City