# Interview question: How do you handle imbalanced data?

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Source: https://www.aced.io/questions/3531/handle-imbalanced-data
Source observed: 2026-11-05T00:16:27.206Z
Last checked: 2026-11-05T00:16:27.206+00:00
Indexed: 2026-11-06T01:11:35.453+00:00

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# How do you handle imbalanced data?

We publish this **Concept** interview question for **Product Manager**, **Data Scientist**, and **Machine Learning Engineer** candidates. It is associated with **Hubspot**, **The Trade Desk**, and **JP Morgan Chase**. The question shows **3 interviews** and was last reported as asked **2 years ago**.

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## Interview experiences

Two shared experiences are attached to this question:

- [Hubspot — 2 years ago](https://www.aced.io/experiences/hubspot-product-manager-interview-a8f144): “Process was smooth. Recruiter was incredible and very communicative. They provided good verbal feedback and enough tips on each round to adequately prepare. People I interviewed with were all kind and seemed neutral vs certain companies where it feels like they want you to fail.” **Product Manager · Mid Level / L4**
- [The Trade Desk — 2 years ago](https://www.aced.io/experiences/the-trade-desk-data-scientist-interview-9b14db): “Overall, the interview process was pretty straightforward and well organized. The interviewers were friendly and gave me a good opportunity to talk through my experience and approach to problems. The process was a little lengthy, but overall it was a positive experience.” **Data Scientist**

## Community answers

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## Related questions

- [Given imbalanced training data, how do you prevent overfitting?](https://www.aced.io/questions/3420/prevent-overfitting-imbalanced-training-data)
- [How do you handle model drift?](https://www.aced.io/questions/6230/explain-handle-model-drift)
- [How do you handle working with ambiguous data?](https://www.aced.io/questions/4998/working-with-ambiguous-data)

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