Data Scientist (AI Training) (Canada)

Data Scientist (AI Training) (Canada)

24 Oct
|
DataAnnotation
|
Canada

24 Oct

DataAnnotation

Canada

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, transparent 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.

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.

Apply now

Hourly rate up to $150+ / hour

Commitment Flexible hours

Type Independent contractor

Payouts Weekly

Apply now

📌 Data Scientist (AI Training) (Canada)
🏢 DataAnnotation
📍 Canada

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