Kaggle Username: Change, Find and Verify

Find a Kaggle contributor’s notebooks, datasets, and competition activity under their public username.

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Last updated October 23, 2026

About Kaggle profiles

How Kaggle usernames work

A Kaggle username is the short handle at the root of the profile address shown above. It is also the owner part of every public dataset and notebook reference, such as username/dataset-name, so links to someone's work carry their username. Kaggle keeps a separate display name next to it, which is the name shown on discussion posts.

Typical profile URL: https://www.kaggle.com/<handle>

Tips for finding accounts

Use the official Kaggle CLI filters kaggle datasets list --user and kaggle kernels list --user to list a contributor’s public work.

Profile visibility

Kaggle shows public notebooks, datasets, models, discussion posts and competition results. Private datasets and notebooks, and team work that is not published, are not visible. ProfileTrace includes Kaggle among the ~4,000 sites it checks for an exact username, but it cannot see private work or confirm who operates an account. Kaggle does not document username changes; contact kaggle.com/contact if the fixed username causes a problem.

More about Kaggle

What this service is

Kaggle is a data science community where members enter competitions, publish notebooks and datasets, and earn progression tiers such as Contributor, Expert or Grandmaster. Because hiring managers often look at Kaggle work, the username tends to follow a person through their portfolio, which is why so many people want to change an early, casual choice.

Username and URL behavior

There is no documented self-service username change on Kaggle, and a feature request titled Ability to Change Usernames has been open on the Kaggle Product Feedback forum since February 2023. Because datasets and notebooks are addressed as username/slug in Kaggle's official API documentation, a changed username would change every link to that work. Your display name is a separate field.

Links and account details

Useful public signals are the dates and topics of notebooks and datasets, competition results, progression tier, and discussion history. Kaggle's Community Guidelines list plagiarism and attempts to manipulate the progression system among behavior that earns warnings, so copied notebooks or suspicious upvote patterns are worth a second look when you assess a profile.

Common impersonation pattern

On Kaggle the risk is less a fake account and more borrowed credibility: a candidate pointing to someone else's Kaggle work, or a profile whose display name matches a known data scientist while the username does not. Since the username is the fixed part, it is the identifier to confirm, not the display name.

How to report a concern

Raise account or content problems with Kaggle through Kaggle's contact page, and review the Kaggle Community Guidelines for what counts as a violation. For hiring checks, ask the candidate to confirm their username directly rather than relying on a name match.

Kaggle Verification Checklist

Check the profile

Confirm the username in the profile address, not just the display name.
Check that the notebooks or datasets being cited list the same username as owner.
Compare the account's activity dates with the period the person says they were active.
Ask the person to share their profile link from their own resume, website or other profile.

What to do with the results

Note the kaggle.com username, its tier and the date you reviewed it.
Keep links to the specific notebooks and datasets you reviewed.
Check the same handle on code hosts and research sites to see a fuller portfolio.
Recheck competition results later, since leaderboards and tiers change over time.

Checks and reporting on Kaggle

Signs of a copied account

A resume that cites Kaggle work under a username the candidate cannot show they control.
Notebooks copied from other users with minimal changes.
A display name that matches a known data scientist on a different username.
Progression that jumps quickly without matching published work.

Check the account

Open a cited notebook and check its version history and the author shown on it.
Look for the same Kaggle username on the person's GitHub, website or other public profiles.
Check whether notebooks are original work or forks of someone else's notebook.
Use the display name only as a hint, since it is separate from the fixed username.

Report a copied account

Save the profile URL and links to the specific notebooks, datasets or discussion posts.
Record the original work if you suspect plagiarism, with its author and date.
Contact Kaggle through kaggle.com/contact with the links.
For hiring decisions, document what you checked and follow your own screening policy.

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