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Zest AI interview questions
3 practice questions in the style of Zest AI's interviews, covering Machine Learning, Coding & Algorithms.
0 easy0 medium3 hard
Zest AI interview questions by the numbers
Last updated
Katkat has 3 Zest AI interview questions. The largest topics are Machine Learning (67%) and Coding & Algorithms (33%). By difficulty: 100% hard. The most common round is Onsite (100%).
Topics
- Machine Learning67% · 2
- Coding & Algorithms33% · 1
Difficulty
- Hard100% · 3
Interview rounds
- Onsite100% · 3
Roles
- Data Scientist100% · 3
Most mentioned in interview experiences
- 1.Build a fair loan classifier1 report
- 2.Compute tree depth and meeting rooms1 report
- 3.Diagnose overfitting from error curves1 report
Counted from 1 candidate interview experiences on Katkat. How we collect and count
Showing 1–3 of 3 results
This question evaluates competency in supervised classification and credit risk modeling, covering data exploration and preparation, model selection, evaluation metrics, threshold setting, fairness and regulatory considerations, interpretability, validation, and monitoring.
Zest AIData ScientistMachine LearningOnsiteThis question evaluates skills in tree traversal and recursion for computing maximum depth of a binary tree, alongside interval scheduling and resource allocation for determining the minimum number of meeting rooms, testing reasoning about data structures such as trees and interval endpoints.
Zest AIData ScientistCoding & AlgorithmsOnsiteThis question evaluates the ability to recognize and diagnose model generalization problems—specifically overfitting—by interpreting training, validation, and test error curves and understanding validation procedures and sources of variance.
Zest AIData ScientistMachine LearningOnsite
Zest AI interview experiences
All 1 →- Eight Rounds, Then Ghosted by a Vanishing HRZest AI · Data Scientist · Onsite · Apr 2026No response
Let me share the funniest interview experience I've had recently. I saw the posting online and applied on a whim. The recruiter emailed me to reach out. From start to finish there were 8 rounds total. Yes, 8, for a company this small. First was the hiring manager round: resume and machine learning concepts. Then a technical screen. The first question showed a graph where training, testing, and va…
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