How to get involved

How data scientists and companies can get involved

Competition Topics

There are two ways in which bitgrit prepares challenges for data science competitions. One is when a sponsor company already has a problem they want to solve. The other is when bitgrit independently sets challenges that are either currently needed or likely to be needed in society.

When a company already has a problem they want to solve, the process is straightforward. The challenge is used in the competition as it is, or with modifications (if the company does not want to publicly disclose their own challenges), according to the needs of the copmany. On the other hand, when bitgrit independently sets challenges, they are based on discussions among members with diverse backgrounds such as the marketing department and machine learning engineers. The goal is to set challenges that are likely to become popular topics or will be needed in society in the future, and the data is prepared through unique channels.

The steps to join the competition

The steps for a data scientist to participate in a competition are fairly straightforward. First, they register their email address on bitgrit's data science platform. Once the registration is complete, they can access the competition data by accepting the NDA for the ongoing competition and participate. Please note that it is not possible to register multiple accounts using the same email address, and participating in competitions with multiple accounts using multiple email addresses is strictly prohibited. Additional security measures are listed as part of the “Anti-exploit measures” section.

In order to enter a competition, each Data Scientist wishing to participate would be required to deposit or stake a set amount of BGR tokens. After the end of each competition, each participating data scientist will receive a portion of their staked BGR back by way of a tiered ranking system. The amount of BGR returned will vary per competition.


The "leaderboard" in a data science competition is a ranking system that publicly displays the performance of participants' models based on specified evaluation metrics such as accuracy or F1 score. The leaderboard indicates how well participants' models perform compared to other participants. The benefits of using a leaderboard in a competition are as follows:

1. Motivation: The leaderboard stimulates competitiveness and provides participants with the motivation to strive for better results. Seeing their own rank and its changes on the leaderboard serves as a driving force for participants to invest time and effort into improving their position.

2. Visibility: High ranks on the leaderboard enhance visibility and recognition within the data science community. Participants' names may gain attention and they may be recognized as exceptional data scientists by companies and potential employers, contributing to the activation of both participants and the community as a whole.

3. Eligibility for rewards: In bitgrit competitions, participants who achieve top rankings are eligible for rewards. The leaderboard plays a critical role in determining the winners (as well as detecting fraudulent activities) and deciding the eligibility for rewards. This aspect is important for participants to compete either for recognition or monetary rewards.

As a new feature to further enhance data science competitions in the future, it is also being considered to provide a platform for participants to exchange information. In such a platform, participants who have achieved top rankings can engage in discussions with one another, allowing them to learn approaches and techniques they may not have been aware of. Such an exchange platform provides a cooperative environment where participants can discuss strategies, share ideas, and learn from each other.

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