Clinical Data Scientist - AI Trainer

Role overview

This opportunity is for experienced quantitative professionals who can help improve AI models. You will assess AI-produced analytical work, tackle technical challenge tasks, and share feedback that influences how the systems handle data, modelling, and scientific reasoning. The role is suitable for people with backgrounds such as data science, astrophysics, economics, biostatistics, operations research, or other quantitative disciplines. Some contributors do this alongside another full-time job, while others treat it as their main work.

How the process works

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

What the work involves

• Review AI-generated quantitative outputs for correctness and practical soundness, including statistical analysis, predictive modelling, scientific reasoning, and data-based insights.
• Create and solve quantitative tasks used to train and benchmark AI systems in areas such as forecasting, experimental analysis, optimisation, and statistical inference.
• Produce clear technical write-ups and maintain well-organised analytical code.
• Share feedback that helps improve the next generation of AI systems designed for quantitative reasoning.

Candidate profile

Applicants should have at least 2 years of practical experience in a quantitative role or research setting. Suitable backgrounds include data science, statistics, economics, finance, physics, biology, epidemiology, operations research, and related fields. Coding experience is needed, along with the ability to write and review analytical code from start to finish. You should also be comfortable with statistical techniques, predictive modelling, and experiment design such as A/B testing, hypothesis testing, regression, classification, and time-series forecasting. Strong English fluency, including native- or bilingual-level writing, is required. A bachelor’s degree in a quantitative subject is preferred, while a master’s degree or PhD is an added advantage. Demonstrated credentials such as Kaggle rankings or AWS/GCP machine learning certifications are also beneficial.

Contract terms and benefits

This is an independent contractor engagement. You can select the projects you want to take on and decide when you work. The role is handled on your own schedule, on your own computer, from home. Project pay starts at USD 50 to USD 100+ per hour, with bonus rates available on certain projects. Payments are issued through PayPal, which also handles any currency conversion from USD. No payment is ever requested from applicants.

Eligibility

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

Additional information

The role is tagged under data science. The position is described as onsite in the source data, but the job details clearly state that work is done from home on your own computer.