[Remote] Health Data Analyst - AI Trainer

Note: The job is a remote job and is open to candidates in USA. DataAnnotation is seeking experienced quantitative professionals to contribute to the development of cutting-edge AI systems. As a Health Data Analyst - AI Trainer, you will evaluate AI-generated quantitative work and provide feedback to enhance AI models' reasoning capabilities.

Responsibilities

• Evaluate AI-generated quantitative work, including statistical analysis, predictive modeling, scientific reasoning, and data-driven insights, for technical accuracy and real-world validity
• Design and solve quantitative problems used to train and benchmark AI systems, spanning areas like forecasting, experimental analysis, optimization, and statistical inference
• Write clear technical explanations and well-documented analytical code
• Provide feedback that directly shapes the next generation of AI models built for quantitative reasoning

Skills

• 2+ years of hands-on experience in a quantitative role or research environment — such as data science, statistics, economics, finance, physics, biology, epidemiology, operations research, or any adjacent field
• Some coding experience required, with comfort writing and reviewing analytical code end-to-end
• Practical experience with statistical methods, predictive modeling, and experiment design (e.g., A/B testing, hypothesis testing, regression, classification, time-series forecasting)
• Fluency in English (native or bilingual level) with strong writing skills
• A bachelor's degree in a quantitative field is preferred (Statistics, Computer Science, Mathematics, Engineering, or similar); a master's or PhD is a plus
• Relevant credentials are a plus (e.g., Kaggle Competition ranking, AWS/GCP ML certifications, or equivalent demonstrated expertise)

Benefits

• Fully remote: work from anywhere in the US, Canada, UK, Ireland, Australia, and New Zealand.
• Flexible schedule: choose which projects you take on and when you work.
• Impact: help shape the future of AI systems built to reason about data and analytics.

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