Analytics Engineer - AI Trainer

DataAnnotation is offering a remote contract role for an Analytics Engineer - AI Trainer. You will help train AI models by evaluating quantitative outputs, crafting training problems, and providing actionable feedback to improve AI systems. The arrangement emphasizes flexibility, autonomy, and the chance to influence data-driven AI reasoning from anywhere.

Benefits

• Fully remote: work from anywhere in the United States, Canada, United Kingdom, Ireland, Australia, and New Zealand.
• Flexible schedule: select projects and set your own hours, using your own computer from home.
• Competitive pay: hourly rates range from $50 to $100, with potential bonus rates on selected projects.
• Impact: contribute to the development of AI systems designed for quantitative reasoning and analytics.
• Payment is processed via PayPal. Eligible locations are the US, Canada, UK, Ireland, Australia, and New Zealand.

Responsibilities

• Evaluate AI-generated quantitative outputs for technical accuracy and real-world validity, covering statistical analysis, predictive modeling, scientific reasoning, and data-driven insights.
• Design and solve quantitative problems used to train and benchmark AI systems, spanning forecasting, experimental analysis, optimization, and statistical inference.
• Produce clear technical explanations and maintain well-documented analytical code.
• Provide feedback that informs the next generation of AI models built for quantitative reasoning.

Requirements

• 3+ years in a quantitative role or research environment, such as data science, statistics, economics, finance, physics, biology, epidemiology, operations research, or related fields.
• Some coding experience with comfort in writing and reviewing analytical code end-to-end.
• Hands-on experience with statistical methods, predictive modeling, and experiment design (A/B testing, hypothesis testing, regression, classification, time-series forecasting).
• Fluency in English with strong writing skills.
• Bachelor’s degree in a quantitative field is preferred; advanced degrees (Master’s or PhD) are a plus.
• Relevant credentials are advantageous (eg, Kaggle rankings, AWS/GCP ML certifications, or equivalent demonstrated expertise).