Data Scientist - AI Trainer

DataAnnotation is seeking an experienced Data Scientist - AI Trainer to support the evaluation and development of AI systems focused on quantitative reasoning. In this fully remote contract role, you will review AI-generated quantitative work, help build training and benchmarking problem sets, and deliver feedback that improves model performance.

Role overview

As an AI Trainer, you will assess technical outputs for accuracy and real-world validity across statistical analysis and predictive modeling. You will also design quantitative tasks that support forecasting, experimental analysis, optimization, and statistical inference, then provide clear explanations and documented code to support the platform’s workflow.

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, covering areas such as forecasting, experimental analysis, optimization, and statistical inference.
• Write clear technical explanations and well-documented analytical code.
• Provide feedback that directly influences the next generation of AI models built for quantitative reasoning.

Requirements

• 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 a closely related field.
• Some coding experience with comfort writing and reviewing analytical code end-to-end.
• Practical experience with statistical methods, predictive modeling, and experiment design (examples include A/B testing, hypothesis testing, regression, classification, and time-series forecasting).
• Fluency in English (native or bilingual) 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, including Kaggle Competition ranking and AWS/GCP ML certifications or equivalent demonstrated expertise.

Tech stack

• Kaggle
• AWS
• GCP
• PayPal

Location, schedule, and pay

• Location: Massachusetts (remote)
• Job type: contract
• Schedule: flexible, with paid, assessment-gated work on the platform
• Pay: USD 50–100 per hour (projects are paid hourly; up to $60 USD per hour, with higher-paying opportunities available based on performance)

Where you can work from

• United States
• Canada
• UK
• Ireland
• Australia
• New Zealand

Notes

• Payment is made via PayPal.
• DataAnnotation will never ask for any money from you.
• This role is only available to candidates in the regions listed above.