Statistical Analyst - AI Trainer

Role Overview

This opportunity is for seasoned quantitative professionals who want to contribute to the development of AI systems. The work involves collaborating with advanced models on tasks such as checking AI-produced quantitative analysis, resolving technical challenges, and giving feedback that helps improve how these systems handle data, modelling, and scientific reasoning.

Candidates from fields like data science, astrophysics, economics, biostatistics, operations research, and other quantitative disciplines may be a strong fit. The role can suit people who want to combine it with another full-time position as well as those looking for it to be their main work.

How the 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 confirmation by email and paid tasks will be made available through the platform.

Contracting Benefits

• You decide which projects to take on and when to work on them.
• You can work independently from your own computer and set your own schedule from home.
• Compensation is paid on an hourly basis, with rates beginning at USD 50-100+ per hour on selected projects, and some projects may include bonus pay.

Responsibilities

• Review AI-created quantitative outputs for accuracy, including statistical analysis, predictive modelling, scientific reasoning, and evidence-based insights.
• Create and solve quantitative tasks used to train and evaluate AI systems across forecasting, experiment analysis, optimisation, and statistical inference.
• Prepare concise technical write-ups and maintain clear, well-organised analytical code.
• Share detailed feedback that helps improve the next generation of AI models for 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 area.
• Working coding knowledge and the ability to write and review analytical code from start to finish.
• Hands-on familiarity with statistical techniques, predictive modelling, 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 ability.
• A bachelor’s degree in a quantitative discipline such as Statistics, Computer Science, Mathematics, Engineering, or a comparable field is preferred; a master’s degree or PhD is an added advantage.
• Additional credentials are beneficial, such as Kaggle competition rankings, AWS/GCP machine learning certifications, or similar evidence of expertise.

Additional Information

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

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