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."
Segment 500k users into three groups
Churn-Risk Segmentation to Maximize Expected 90-Day Revenue You must segment 500,000 users into three contiguous groups along a churn-risk score, orde...
Design a robust pro-ranking A/B test
Experiment Design: Evaluating a New Pro Ranking Algorithm (Ranker) in a Two‑Sided Marketplace You are designing an experiment to evaluate a new pro ra...
Evaluate shopping tab pre- and post-launch
Instagram Shopping Tab — Measuring Off‑App Purchases, Opportunity Sizing, and Launch Readout Context Instagram is planning a new Shopping tab. Users o...
Design metrics and experiment for Shopping launch
Experiment and Metric Plan: New Shopping Module Embedded in the Pins Feed Context You are introducing a Shopping module directly into the Pins feed. T...
Design robust metrics for a feature launch
A/B Test Metrics and Guardrails for Quick Reply (1-week) Context You are adding a Quick Reply feature (suggested reply chips in the DM composer) to a ...
Design an experiment for thermal bags
Experiment Design: Thermal Bags for Couriers to Reduce Cold-Food Refunds Background We want to evaluate whether providing couriers with thermal bags r...
Design an A/B test for pre-roll ads
A/B Test: Reduce Mobile Live‑Stream Pre‑Roll Ad Frequency by 20% Context: You are designing an experiment on mobile live streams to evaluate reducing ...
Decide launch with asymmetric costs
Launch Decision Under Asymmetric Costs (Experiment p=0.10) Context You ran an A/B test on a churn‑reduction feature. The test's p‑value was 0.10 (sugg...
Build cohort 30-day retention from signup date
This question evaluates a data scientist's competency in cohort analysis, retention metric computation, handling right-censoring and edge-case treatme...
Design and analyze email deliverability experiment
This question evaluates a data scientist's competency in experimental design, causal inference, sequential testing (frequentist and Bayesian), instrum...
Evaluate a model and choose metrics
Fraud-screening model evaluation under class imbalance and asymmetric costs Context You operate a binary classifier that flags e‑commerce orders for m...
Drive product decisions with causal product sense
Experimenting on a New Paywall with Likely Spillovers Context You are designing an experiment to evaluate a new paywall on a social/content app where ...
Design and power a frequency-cap experiment
Experiment Design: Raising a 7‑Day Frequency Cap from 3→4 Impressions Context A large video ad campaign plans to raise the per‑user rolling 7‑day freq...
Evaluate fake accounts and ad creation
This question evaluates a data scientist's competencies in measurement and experimentation, covering prevalence estimation and detection system evalua...
Define engagement metrics and analyze comment distribution
You are a Data Scientist for a video platform. A PM asks you to: 1) Define metrics for “engagement” (they want a clear metric framework they can use i...
How to debug an apparent D14 retention drop
Scenario A dashboard shows D14 retention (users retained on day 14 after signup/first activity). In the last week, the chart shows a sharp decline. As...
Should you roll out if NSM decreases?
Scenario You ran an experiment. The north star metric (NSM) is profit per order. Observed results - Average order volume increased in treatment vs con...
Assess Adding Bicycle Dashers
DoorDash is considering allowing bicycle couriers (bike dashers) to fulfill deliveries in a city that is currently served mostly by car/scooter dasher...
Should a Restaurant Partner with Groupon?
This question evaluates the ability to analyze unit economics, marginal profitability, and cannibalization effects using quantitative assumptions and ...
LinkedIn Product Case Opportunity Sizing
LinkedIn Product Case: Segmentation, Opportunity Sizing, and Adoption Prediction You are interviewing for a Data Scientist role focused on analytics a...