Data Scientist

Overview

The newest models can spin up a full analysis in minutes — load the data, pick a method, produce charts and a confident conclusion. Someone has to check whether the statistics actually hold up, and that someone is you.

As a Data Scientist you’ll evaluate AI-generated analyses on real datasets, stress-test the reasoning behind them, and write the judgments that teach the next generation of models what rigorous data work looks like.

What you’ll actually do

• Evaluate AI-built analyses on real datasets: the method choice, the assumptions, and whether the conclusion actually follows from the numbers.
• Red-team the statistics to expose leakage, p-hacking, confounded comparisons, and confident nonsense before real users trust them.
• Write the better analysis when the model falls short: sound methodology, honest uncertainty, clear takeaways.

Roles this fits

Common backgrounds: Data Scientist, Data Analyst, Analytics Engineer.

What we look for

• Professional or academic experience doing real data analysis — industry, research, or serious independent work.
• Fluency with the standard toolkit; most tasks use Python, SQL, and notebooks.
• Clear written English: your explanations are the training signal.
• No degree required. We care about what you can do, not where you learned it.

How it works

Apply

Qualify

Work & get paid

Compensation

Up to $75 – $150+/hr depending on task difficulty and specialization. Many contributors add $10k–$100k+ a year; some make it their full-time income.

About DataAnnotation

DataAnnotation is where 100k+ experts train the world’s leading AI models. $150M+ paid to contributors to date, and the average contributor stays 5+ years. Flexible, remote, and always project-available.