Data Scientist Analytics & Experimentation Interview Questions
Practice 895 real Analytics & Experimentation interview questions for Data Scientist roles. From companies including Meta, Capital One, DoorDash, Uber, TikTok.
"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."
Decide best email variant using stratified A/B analysis
Stratified A/B Test Across Two Strata (Week/Location) You ran an email A/B test across two strata defined by week/location. Each user receives at most...
Recover causal effect without a control group
Post-hoc Causal Estimation After a Failed A/B Rollout Context An intern accidentally shipped a feature to 100% of eligible users for 5 consecutive day...
Design and analyze an ads ranking experiment
This question evaluates a data scientist's experimental-design and causal-inference skills applied to ad ranking, including sample-size estimation, va...
Decide on vegan-burger R&D investment
Investment Decision: Vegan Burger R&D and Launch Business Case You are evaluating whether to invest now in R&D to develop and launch a plant-based (ve...
Evaluate Key Metrics for Capital One Ad Campaign
Evaluate Key Metrics for Capital One Ad Campaign Streaming Ad Campaign Evaluation and ROI Comparison Context You are evaluating a credit-card marketin...
Evaluate Alternative Data for an Investment Pitch
You are given an alternative dataset and asked to develop an investment pitch. Describe how you would determine whether the data contains a real, usab...
How would you evaluate adding video ads?
You are a data scientist for a free-to-play mobile game. The product team wants to introduce video ads (e.g., rewarded videos and/or interstitial vide...
Improve TikTok's Algorithm for Diverse Content Discovery
Product Feedback and Experimentation: Diverse Content Discovery You are a frequent TikTok user interviewing for a Data Scientist role focused on analy...
Investigate cross-country engagement and ads experiments
This Analytics & Experimentation (Data Scientist) question evaluates skills in experiment design and causal inference, metric definition and trade-off...
How would you evaluate a free-trial A/B test?
You run an online marketing experiment to evaluate whether offering a free 1‑month trial increases growth. Experiment context - Eligible visitors are ...
Should WhatsApp launch group calls?
This question evaluates a data scientist's skills in experiment design, product analytics, metric definition, causal inference, and managing network e...
Analyze homepage drop and feed ranking
You are interviewing for a product data science role at LinkedIn. Answer the following two product-sense questions. 1. Diagnose a drop in Home Page ->...
How would you diagnose a completed orders drop?
This question evaluates a candidate's ability to diagnose a drop in completed orders in a two-sided marketplace, emphasizing competencies in data anal...
Define and critique a user activity metric
This question evaluates a candidate's ability to design and critique user-activity metrics, covering event-level instrumentation, metric validity, and...
Analyze Trends to Optimize Pirate-Theme Product Strategy
Analyze Trends to Optimize Pirate-Theme Product Strategy Scenario You have explored and summarized the performance of the "Pirate" theme for the Shopi...
Measure impact of ads-manager automation feature
This question evaluates competency in causal impact measurement, experimental design, metric selection, monitoring instrumentation, and bias identific...
Design evaluation when A/B test is impossible
This question evaluates a data scientist's competency in causal inference, observational experiment design, metric selection, and production monitorin...
Assess card rewards profitability and break-even spend
Credit Card Unit Economics and Break-even Spend Context A bank is evaluating launching a credit card that pays 1% rewards on all purchases. Consider p...
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...