Google Data Scientist Machine Learning Interview Questions
Practice 28 real Machine Learning interview questions for Data Scientist roles at Google.
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Model Soccer Shot Conversion
You are given event-level soccer shot data, and possibly tracking or contextual data. Build a model that predicts the probability that a shot becomes ...
Design a battery-life predictor and cold-start strategy
Smartphone Time-to-Empty (TTE) Prediction — Baseline, Features, Cold Start, Evaluation, and Monitoring Context You are building a per-device predictor...
When do you use mixed-effects models
You are modeling a user outcome (e.g., watch time or retention) across many countries and many users. Observations are nested (multiple days per user;...
Model Shot Success by Location
You need to build a model that predicts the probability that a shot becomes a goal for every location on a soccer field. Assume you have historical sh...
Build and evaluate a full ML pipeline
You must predict both (1) probability that a user will spend >$0 in the next 7 days (classification) and (2) expected spend in the next 7 days (regres...
Build and evaluate bad-link classifier
You have 1,000 URLs labeled as bad or good and a much larger unlabeled pool, with bad links rare. Design features and train a logistic regression. Exp...
Find companies similar to a given client
System Design: Retrieve Top-20 Most Similar Companies for Sales Prospecting You are given an anchor client (e.g., The Coca‑Cola Company). Design a sys...
Estimate b when features exceed samples
Consider the linear model y = Xb + ε with X ∈ R^{n×(m+1)} including an intercept. a) Derive the OLS estimator b̂ = (XᵀX)^{-1}Xᵀy, stating the rank con...
Predict and act on contract renewal risk
Predicting Enterprise Contract Renewal After a Quality Incident Context A video-conferencing provider experienced a spike in call disconnects. You nee...
Handle highly imbalanced classification data
You must build a binary classifier for fraud with a 0.2% positive rate and 10M rows × 500 features. Propose an end-to-end plan that covers: 1) data sp...
Build and evaluate illegal-video classifier
End-to-End ML System Design: Flag Illegal YouTube Videos You are tasked with designing a production ML system to detect and triage potentially illegal...
Handle p≈n linear regression with L1
You must fit linear regression with p = 500 predictors and n = 600 observations. What failure modes do you expect and why does OLS overfit when p is c...
Decide between two vendors under constraints
You have two third‑party search vendors, A and B, plus historical order‑level data: lead_time_days, unit_price, on_time_rate, defect_rate, min_order_q...
Diagnose and fix flawed model fit
Fixing a Churn Classifier: Encoding, Imbalance, Evaluation, and Fairness Context You inherit a binary classifier that predicts churn=1. The current im...
Design and critique an abuse-detection ML system
ML System Design: Abusive Content Detection and Triage (Trust & Safety) Context: You are designing an ML system to identify and triage abusive content...
Compare Logistic Regression and Random Forest in Limited Data Scenarios
Model Selection for Binary Classification with Limited Data and Potential Non-Linearities Scenario You are designing a binary classifier with limited ...
Explain linear regression to non‑technical stakeholders
Explain linear regression to a non-technical executive using a concrete business example (e.g., predicting weekly sales from price, ad spend, and stor...
Explain logistic regression vs forests and boosting
Technical Screen — Machine Learning Answer all parts precisely. 1) Binary logistic regression: model, loss, gradient, convexity - Define the model: p(...
Explain a favorite model end-to-end
Predictive Model Deep-Dive (End-to-End) Pick one predictive model you know deeply (e.g., logistic regression, gradient-boosted trees, transformer clas...
Detect Overfitting or Underfitting in Logistic Regression Models
Logistic Regression Bias–Variance in High‑Dimensional Ads Prediction Scenario You are building a large‑scale binary classifier (e.g., click/conversion...