Climate Scientist - AI Trainer

About the role

This opportunity is for quantitative specialists who can help improve AI systems by reviewing and training them on complex analytical work. In this position, you will assess machine-generated quantitative analyses, tackle technical problem-solving tasks, and share feedback that influences how AI models handle data, modeling, and scientific reasoning. Experience from fields such as data science, astrophysics, economics, biostatistics, operations research, or other quantitative disciplines can be relevant if you are comfortable working rigorously with data and models. Some contributors use this as a side engagement alongside another full-time job, while others make it their main focus.

To begin, you will complete a short assessment after creating an account. This acts as the screening step. If successful, you will receive confirmation by email and paid tasks will appear on the platform.

What contracting with the company offers

• You can pick the projects you want to take on and decide when to work on them.
• The work can be done on your own schedule, using your own computer, from home.
• Pay starts at USD 50 to USD 100+ per hour, and some assignments include additional bonus rates.

Responsibilities

• Review AI-produced quantitative outputs for correctness, including statistical analysis, predictive models, scientific conclusions, and data-backed insights.
• Create and solve quantitative tasks that help train and evaluate AI systems across forecasting, experimental design, optimization, and statistical inference.
• Produce concise technical write-ups and maintain clear, 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 job or research setting, such as data science, statistics, economics, finance, physics, biology, epidemiology, operations research, or a similar area.
• Basic programming ability is required, along with confidence in writing and reviewing analytical code from start to finish.
• Hands-on familiarity with statistical techniques, predictive modeling, and experiment planning, including A/B testing, hypothesis testing, regression, classification, and time-series forecasting.
• Strong English fluency at native or bilingual level, plus excellent written communication.
• A bachelor's degree in a quantitative subject is preferred, such as Statistics, Computer Science, Mathematics, Engineering, or a related field; a master's degree or PhD is an advantage.
• Additional proof of expertise is beneficial, including examples such as Kaggle rankings, AWS or GCP machine learning certifications, or similar credentials.

Payment and engagement terms

Compensation is processed through PayPal. You will not be asked to pay any fee at any stage. Any currency conversion from USD is handled by PayPal. This role is open only to applicants located in the United States, Canada, the United Kingdom, Ireland, Australia, and New Zealand. The arrangement is as an independent contractor.