Google Data Scientist Analytics & Experimentation Interview Questions
Practice 36 real Analytics & Experimentation 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."
Evaluate AI Workflow Product Metrics
This question evaluates product analytics and experimentation skills—specifically metric definition, funnel construction, segmentation, instrumentatio...
Design an A/B test for search ranking
This question evaluates a data scientist's competency in online experimentation, causal inference, product analytics, and operational metrics engineer...
Design an Unbiased Upgrade Experiment
This question evaluates understanding of causal inference, experiment design, and metric selection in product analytics, including defining causal est...
How would you use propensity score matching here
You want to estimate the causal effect of a new recommender feature on 7-day retention. The feature was not randomized: users “opt in” after seeing a ...
How do you diagnose a ratio metric change
In an A/B test, the treatment group shows a statistically significant increase in a ratio metric: - CTR = clicks / impressions increased by +1.2% rela...
Design tests to measure latency impact
Question You are a Data Scientist supporting a large consumer product (e.g., YouTube). Engineering ships a change intended to reduce client-side / vid...
Design a Causal Upgrade Experiment
This question evaluates competency in causal inference and experimental design, focusing on handling selection bias, defining intent-to-treat and trea...
Define and apply Gmail user segments
Question Gmail wants to create actionable user segments to drive both product improvements and marketing/lifecycle outcomes. Propose a segmentation sc...
Diagnose and reverse an adoption-rate decline
Problem: Investigating a 7pp Drop in Google Meet Enterprise Adoption Rate Context Over the last 4 calendar weeks, enterprise adoption rate has fallen ...
Design an A/B test with guardrails and SRM checks
You are launching a new personalized ranking on the product listing page. Define: (a) the primary success metric and its exact formula (include numera...
Diagnose a metric drop in search time
Over the last 3 calendar months, the metric 'searching time per user per session' dropped by 35%. A teammate proposes modeling two distributions: T1 =...
Design long-tail search evaluation under label budget
Estimating ΔNDCG@10 With Limited Labels Under a Heavy-Tailed Query Mix You serve ~100M queries/day. Query frequencies follow a Pareto distribution wit...
Experimentally evaluate jogging-route recommendations
Design an Evaluation for Jogging Route Recommendations in Maps Objective Design an A/B test and evaluation framework for recommending optimal jogging ...
Design pricing and multivariate button experiments
You join a B2B SaaS firm with three public tiers (Basic $25/month, Pro $50/month, Enterprise = sales-quoted). The PM asks for a 2‑week A/B test to rai...
Design A/B Test for Google Maps UI Change
Design A/B Test for Google Maps UI Change A/B Test Design: Moving the Google Maps Search Bar to the Bottom Context Google Maps is considering a UI cha...
Compare two stores’ profits rigorously
Prompt: 14-Day Plan to Decide Which Snack Shop Will Be More Profitable Next Quarter Context: Two snack shops operate simultaneously at a school gate. ...
Assess education–income effect credibly
This question evaluates a data scientist's competencies in causal inference, experimental design, model selection, estimand specification (ATE) and se...
Measure causal impact of YouTube ads
This question evaluates causal inference and experimental design skills for marketing measurement, including competency in identifying confounders, de...
Diagnose unbiasedness in a messy A/B test
This question evaluates a data scientist's ability to diagnose unbiasedness of an intent-to-treat (ITT) estimator in A/B testing under noncompliance, ...
Analyze time series and design validation experiment
This question evaluates competency in time series analysis, change-point detection, count-based forecasting, causal inference and experiment design, a...