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
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Work & get paid

Compensation
Up to $150+/hr depending on task difficulty and specialization. Many contributors add $100k–$200k a year; some make it their full-time income.
About DataAnnotation
DataAnnotation is where 1M+ experts train the world’s leading AI models. Hundreds of millions paid to contributors to date, and the average contributor stays 5+ years. Flexible, remote, and always project-available.
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