Google Data Scientist Statistics & Math Interview Questions
Practice 32 real Statistics & Math interview questions for Data Scientist roles at Google.
"I got asked a hardcore MCM DP question and I saw it on PracHub as well. Solved that question in 5 minutes. Without PracHub I doubt I could solve it in 5 hours. Though somehow didn't get hired, perhaps I guess I solved it too fast? /s"
"Believe me i'm a student here jn US. Recently interviewed for MSFT. They asked me exact question from PracHub. I saw it the night before and ignored it cause why waste time on random sites. I legit wanna go back and redo this whole thing if I had chance. Not saying will work for everyone but there is certainly some merit to that website. And i'm gonna use it in future prep from now on like lc tagged"
"10 years of experience but never worked at a top company. PracHub's senior-level questions helped me break into FAANG at 35. Age is just a number."
"I was skeptical about the 'real questions' claim, so I put it to the test. I searched for the exact question I got grilled on at my last Meta onsite... and it was right there. Word for word."
"Got a Google recruiter call on Monday, interview on Friday. Crammed PracHub for 4 days. Passed every round. This platform is a miracle worker."
"I've used LC, Glassdoor, and random Discords. Nothing comes close to the accuracy here. The questions are actually current — that's what got me. Felt like I had a cheat sheet during the interview."
"The solution quality is insane. It covers approach, edge cases, time complexity, follow-ups. Nothing else comes close."
"Legit the only resource you need. TC went from 180k -> 350k. Just memorize the top 50 for your target company and you're golden."
"PracHub Premium for one month cost me the price of two coffees a week. It landed me a $280K+ starting offer."
"Literally just signed a $600k offer. I only had 2 weeks to prep, so I focused entirely on the company-tagged lists here. If you're targeting L5+, don't overthink it."
"Coaches and bootcamp prep courses cost around $200-300 but PracHub Premium is actually less than a Netflix subscription. And it landed me a $178K offer."
"I honestly don't know how you guys gather so many real interview questions. It's almost scary. I walked into my Amazon loop and recognized 3 out of 4 problems from your database."
"Discovered PracHub 10 days before my interview. By day 5, I stopped being nervous. By interview day, I was actually excited to show what I knew."
"I recently cleared Uber interviews (strong hire in the design round) and all the questions were present in prachub."
"The search is what sold me. I typed in a really niche DP problem I got asked last year and it actually came up, full breakdown and everything. These guys are clearly updating it constantly."
Measure Bird Species Segregation
You are a data scientist analyzing bird observations from a forest. The ecology team wants to know whether different bird species are spatially segreg...
Estimate weather’s effect on mental health
This question evaluates causal inference and applied statistical modeling skills—specifically defining outcomes and treatments, addressing confounding...
Explain Bootstrap and Statistical Inference
This question evaluates a data scientist's competence with resampling methods (bootstrap), uncertainty quantification and hypothesis testing (variance...
Can bootstrap help reduce variance
An interviewer asks: “Can bootstrap help reduce variance?” Answer this question precisely. Distinguish between: 1) Using the bootstrap to estimate var...
Explain Bootstrap and Prove Uniformity
This question evaluates mastery of statistical inference and probability theory, testing knowledge of resampling methods (bootstrap), interpretation o...
Compute precision under noisy annotators
This question evaluates understanding of statistical performance metrics and label-noise propagation by requiring computation of precision, recall, an...
Estimate population singletons from a 10% log
A daily search log has one row per query string. You draw a 10% simple random sample of rows without replacement. Define a “unique query” (singleton) ...
Infer causal impact without an A/B test
Evaluate Impact of a Shipped Version on Disconnections (No A/B Holdout) Context A new client version was shipped system-wide with the goal of reducing...
Estimate unbiased ad scores with many reviewers
This question evaluates a candidate's skills in hierarchical and mixed-effects modeling, latent-variable estimation, debiasing rater severity and scal...
Prove OLS invariance to linear transforms
You fit Model 1: y ~ X1 + X2. You also fit Model 2 using Z = [X1 − X2, X1 + X2] = X T where T = [[1,1], [−1,1]] (2×2, invertible). a) Prove that OLS p...
Compute p-values, probabilities, and regularization choices
Answer all parts. A) Hand‑compute a two‑sided p‑value comparing two means using Welch’s t‑test. Sample A: n1=20, mean1=5.2, sd1=1.1. Sample B: n2=24, ...
Understand Simpson's Paradox with Simple Examples
Understand Simpson's Paradox with Simple Examples Scenario You are a data scientist advising a product team on statistical analysis and experimental d...
Narrow a confidence interval for a mean
You have a simple random sample with n = 100 and sample mean 100. The current 95% CI for the population mean is 100 ± 10, which a PM says is too wide....
Analyze data duplication effects in linear regression
OLS With Duplicated Observations: Estimator, Variance, and Inference Pitfalls Context: You have the linear model y = Xβ + ε with full-rank X ∈ ℝ^{n×p}...
Analyze Linear Regression Changes with Duplicated Observations
Linear Regression, P-values, and Chi-square with Large Samples You are analyzing regression and goodness-of-fit results. Consider what happens if ever...
Infer distribution and choose robust statistics
This question evaluates a candidate's ability to infer underlying distributions from summary statistics and apply robust statistical reasoning includi...
Derive MLEs and conditional Normal distributions
Normal and Bivariate Normal: PDFs/CDFs, MLEs, Conditioning, and Unbiased Variance Setup - Let X1, …, Xn be i.i.d. Normal(μ, σ²). - Independently, let ...
Explain mixed models and fixed vs random effects
In an applied DS setting, you are modeling an outcome (e.g., watch time per session, conversion, or rating) across multiple entities (e.g., users, cre...
Design human review to estimate model accuracy
Design human review to estimate model accuracy You need to estimate the accuracy of an ML classifier on a population of subjects. You can only afford ...
Define and sample a truncated normal
Define the truncated normal Z | a < Z < b for Z ~ N(0,1): write the normalized pdf and cdf. Then design efficient samplers for three cases: (i) a = 1,...