Atmospheric Scientist - AI Trainer

About the Role

This position is for experienced quantitative specialists who can help improve AI systems. You will collaborate with advanced models to review AI-produced quantitative analyses, tackle technical challenges, and share feedback that influences how these systems interpret data, build models, and approach scientific questions. Candidates from atmospheric science and other quantitative backgrounds such as data science, astrophysics, economics, biostatistics, or operations research may be a strong fit if they are comfortable applying rigorous analytical thinking to data and models.

Some contributors do this work alongside another full-time role, while others make it their main focus.

How the Selection Process Works

After creating an account, you will complete a short assessment that acts as the screening step. If you are successful, you will receive an email confirmation and paid assignments will be made available through the platform.

What the Contract Offers

• You can pick the projects you want and decide when to work on them.
• You set your own schedule and work from your own computer at home.
• Hourly project pay starts at USD 50 to USD 100+ per hour, and some projects may include bonus pay.

Key Responsibilities

Your work will focus on reviewing, creating, and improving quantitative tasks that help train and evaluate AI models.

• Check AI-generated quantitative outputs for correctness, including statistical work, predictive modeling, scientific interpretation, and data-based conclusions.
• Build and solve quantitative problems used for training and benchmarking AI systems across forecasting, experimental design, optimization, and statistical inference.
• Prepare understandable technical explanations and maintain well-structured analytical code.
• Share feedback that helps improve the next generation of AI tools for quantitative reasoning.

Candidate Profile

• 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 related discipline.
• Basic coding ability, with confidence writing and reviewing analytical code from start to finish.
• Hands-on exposure to statistical techniques, predictive modeling, and experiment 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 subject such as Statistics, Computer Science, Mathematics, or Engineering is preferred; a master’s degree or PhD is an added advantage.
• Additional proof of expertise, such as a high Kaggle ranking or AWS/GCP machine learning certifications, is beneficial.

Payment and Contract Notes

Compensation is handled through PayPal, and currency conversion from USD will be managed by PayPal if needed. You will never be asked to pay any fee to participate. This is an independent contractor engagement.

Location and Eligibility

Only candidates based in the United States, Canada, the United Kingdom, Ireland, Australia, or New Zealand will be considered.

Category Note

This role sits within the broader data science and quantitative analytics space.