Numerai
A weekly data science tournament where you model obfuscated stock data and can stake NMR crypto on your predictions.
How the 6.6 was reached
- Quality of output6/10
Example repo has 1,187 stars, active push 2026-09-28, MIT; no evidence of prediction performance. github.com
- Ease of use7/10
Python and R example scripts, onboarding tutorials and a CLI; staking crypto adds friction. github.com
- Pricing value8/10
Data and example code are free (MIT); staking NMR is optional. github.com
- API and integration quality6/10
Numerai CLI and Python example submission scripts; full API docs not detailed. github.com
- Solves the problem it claims to solve6/10
Tournament with free obfuscated data works as described; 1,187 stars, no performance evidence. docs.numer.ai
6.6/10 is the mean of the 5 criteria that apply. Scored on the five-criteria rubric v1, 29 September 2026. How scoring works
Pricing
- Free obfuscated dataset
- MIT-licensed example scripts in Python and R
- Optional NMR staking
Key Features
- Obfuscated hedge-fund-grade dataset with targets
- Example scripts in Python and R
- Numerai CLI
- NMR staking with earn or burn based on scores
- Codex agent install via shell script
Pros & Cons
Pros
- Free data and example code
- No finance domain knowledge needed, since data is obfuscated
- Onboarding tutorials for beginners
- Staking is optional
Cons
- No evidence of prediction performance was found
- Staking crypto adds risk and friction
- Full API docs are not detailed
- Not a portfolio or budgeting tool
Numerai suits data scientists who want a real-money modeling contest with free data. Anyone looking for personal finance help or proven returns should look elsewhere, since none is documented here. Treat it as a hobby or research venue.
Try Numerai →Added to scored.tools on
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