Kalshi Data Scientist Interview Questions

The questions to prepare for a Kalshi Data Scientist interview. Questions from real interview reports rank first. Updated weekly.

Feature Engineering and Model Performance

Easy

Explain how feature engineering improves supervised model performance and how to validate its impact with proper evaluation.

Feature EngineeringBias-Variance TradeoffSupervised Learning

Kalshi

Predict Customer Churn

Medium

Build a churn model that flags at-risk customers early using behavioral, billing, and support signals.

Feature EngineeringModel EvaluationSupervised Learning

Kalshi

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Align Analysis to Client Goals

Easy

Framework for keeping marketing analysis tied to client goals, decision needs, and measurable business outcomes.

User NeedsValue PropositionUse Cases

Kalshi

Root Cause Analysis for Market Drop

Medium

Tests structured investigation and data-driven diagnosis for trading activity changes.

root cause analysis

Kalshi

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Discuss Model Evaluation Techniques

Medium

Explain your approach to model evaluation, including how you choose and interpret metrics for different ML problems.

PrecisionAccuracyRecall

Kalshi

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Statistical Significance Methods

Medium

Tests statistical rigor and your ability to choose appropriate significance testing methods.

Hypothesis TestingData AnalysisStatistical Significance

Kalshi

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