Genomics Researcher - AI Trainer

About the role

This opportunity is for quantitative specialists who can help improve AI systems. The work involves reviewing AI-produced quantitative analysis, tackling technical challenges, and giving structured feedback that helps shape how models handle data, modeling, and scientific reasoning.

The role is suited to professionals from fields such as data science, astrophysics, economics, biostatistics, operations research, and similar quantitative disciplines. If you are comfortable reasoning rigorously with data and models, your background may be a strong fit. Some contributors do this alongside another full-time position, while others make it their main work.

To begin, you will create an account and complete a brief assessment that acts as the screening step. If successful, you will receive confirmation by email and paid tasks will become available on the platform.

Key responsibilities

You will review, solve, and improve quantitative tasks used to train AI models, with a focus on accuracy, reasoning quality, and practical validity.

• Assess AI-generated quantitative outputs, including statistical analysis, predictive models, scientific reasoning, and data-based conclusions.
• Create and solve quantitative problems used for model training and benchmarking across forecasting, experimental design, optimization, and statistical inference.
• Produce clear technical write-ups and maintain well-documented analytical code.
• Share feedback that helps refine the next generation of AI systems for quantitative reasoning.

Requirements

• 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 closely related area.
• Working knowledge of coding, with the ability to write and review analytical code from start to finish.
• Hands-on familiarity with 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 written communication.
• 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 advantage.
• Extra credentials, such as a Kaggle competition ranking, AWS/GCP machine learning certifications, or similar proof of expertise, are a plus.

Terms and conditions

This is an independent contractor arrangement. Payment is issued through PayPal, and you will not be asked to pay any money at any stage. PayPal will manage any USD currency conversion. Only applicants located in the United States, Canada, the United Kingdom, Ireland, Australia, or New Zealand will be considered.

Working style and compensation

• You can select which projects to take on and decide when to work.
• The work is completed on your own schedule and from your own computer at home.
• Hourly pay starts at USD 50 to USD 100+, and some projects include bonus rates.