ML Research Scientist - AI Trainer

About the Role

This opportunity is for quantitative specialists who can help improve AI systems by evaluating their outputs and contributing high-quality feedback. The work centers on judging AI-produced quantitative analysis, tackling technical problem sets, and influencing how models reason through data, scientific questions, and analytical tasks. Backgrounds such as data science, astrophysics, economics, biostatistics, operations research, and similar quantitative disciplines are relevant, provided you are comfortable working rigorously with data and models. Some professionals use this as supplemental work alongside another role, while others make it their primary focus.

How the Process Works

After creating an account, you will complete a short assessment that acts as the screening step. Candidates who pass receive email confirmation, and paid assignments then become available on the platform.

Contract Highlights

• You can select the projects you want to take on and decide when to work.
• The role is designed to fit around your own timetable and can be done on your personal computer from home.
• Compensation is hourly, beginning at $50 to $100+ USD per hour, and some projects may include bonus pay.

Responsibilities

• Review AI-generated quantitative work for accuracy and practical relevance, including statistical analysis, predictive modeling, scientific reasoning, and data-based insights.
• Create and solve quantitative problems that help train and evaluate AI systems across forecasting, experimental analysis, optimization, and statistical inference.
• Prepare concise technical write-ups and maintain well-structured analytical code.
• Share feedback that helps improve future AI models focused on quantitative reasoning.

Qualifications

• At least 2 years of practical experience in a quantitative role or research setting, such as data science, statistics, economics, finance, physics, biology, epidemiology, operations research, or a related field.
• Working coding ability, with comfort writing and reviewing analytical code from start to finish.
• Hands-on exposure to statistical techniques, predictive modeling, and experimental design, including A/B testing, hypothesis testing, regression, classification, and time-series forecasting.
• Strong English fluency at native or bilingual level, along with excellent writing skills.
• A bachelor’s degree in a quantitative discipline such as Statistics, Computer Science, Mathematics, Engineering, or a similar area is preferred; a master’s degree or PhD is an advantage.
• Additional proof of expertise, such as a strong Kaggle ranking, AWS or GCP machine learning certification, or similar credentials, is beneficial.

Additional Information

Payment is processed through PayPal, and no money will ever be requested from candidates. Any currency conversion from USD is handled by PayPal. Only applicants based in the United States, Canada, the United Kingdom, Ireland, Australia, and New Zealand will be considered. This is an independent contractor arrangement.

Tags

#datascience