Quantitative Psychologist - AI Trainer

Role overview

This role is for quantitative specialists who want to help improve AI systems. You will collaborate with advanced models on assignments such as assessing machine-generated quantitative reasoning, working through technical challenges, and giving detailed feedback that influences how the models handle data, methods, and scientific problem-solving.

Candidates from fields like data science, astrophysics, economics, biostatistics, operations research, and other numerically focused disciplines are encouraged to apply if they are comfortable reasoning deeply about data and models. Some contributors use this as a side engagement alongside another full-time role, while others make it their main work.

To begin, you will create an account and complete a short assessment that functions like an interview. If successful, you will receive confirmation by email and paid tasks will be made available on the platform.

Key responsibilities

You will review, create, and improve quantitative tasks that help train and evaluate AI models. The work includes checking statistical analyses, predictive models, scientific reasoning, and data-backed conclusions for accuracy and practical validity.

You will also develop and solve quantitative problems covering areas such as forecasting, experimental analysis, optimization, and statistical inference, while producing clear technical write-ups and well-structured analytical code.

In addition, you will provide feedback that helps refine the next generation of AI systems designed for quantitative reasoning.

Qualifications

Applicants should bring 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.

Some coding ability is required, including comfort with writing and reviewing analytical code from start to finish. You should also have practical experience with statistical techniques, predictive modeling, and experiment design such as A/B testing, hypothesis testing, regression, classification, and time-series forecasting.

Strong English communication is essential, with native or bilingual-level fluency and excellent writing skills. A bachelor’s degree in a quantitative discipline such as Statistics, Computer Science, Mathematics, or Engineering is preferred, while a master’s degree or PhD is an advantage. Additional credentials like a strong Kaggle ranking or AWS/GCP ML certifications are considered a plus.

Working arrangement and payment

This is an independent contractor role. Work is flexible: you choose the projects you want to take on and decide when to work. You can complete tasks from your own computer at home.

Compensation is hourly, starting at USD 50 to 100+ per hour, and some projects may include bonus pay. Payments are processed through PayPal, which will also handle any currency conversion from USD. You will never be asked to send money.

Eligibility

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

Additional information

This position is presented as full-time and onsite in the source details, although the work description also emphasizes flexible, home-based project work as an independent contractor.

The role references the topic tag #datascience.