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."
Should We Launch Group Calling?
Question You work on a consumer calling product (think Messenger/WhatsApp-style voice) that currently supports only one-to-one voice calls. The team i...
Diagnose CTR drop after recommendation launch
Experiment Diagnosis: Horizontal Recommendations Carousel on Home Context A new horizontal recommendations carousel was launched on the home page. In ...
Design an experiment for order batching
Experiment Design: Two-Order Batching Policy During Peak Hours Context DoorDash plans to test a dispatch policy that allows a dasher to pick up two ne...
Design Identity-Trust A/B Test
You are interviewing for a Data Scientist role on an Identity & Trust team at a consumer product company. The team wants to launch a feature that stre...
How would you measure impact?
This question evaluates competency in causal inference and experimental design for production analytics, covering delayed outcomes, interference, conf...
Resolve Simpson’s paradox in A/B email test
This question evaluates understanding of Simpson's paradox, causal inference, A/B testing and experimental design within the Analytics & Experimentati...
Present Piracy Trends to a PM
You ran the analyses above and got two preliminary findings: - the monthly pirated-theme usage rate appears to rise from 0% to 100% over the observed ...
Measure Billboard Campaign Impact: Design, Bias, Test Strategy
Measure Billboard Campaign Impact: Design, Bias, Test Strategy evaluates metric design, causal reasoning, experiment setup, diagnostics, SQL/statistic...
Measure a Discovery Boost in a Two-Sided Marketplace
Design a measurement plan for a discovery change in a two-sided marketplace. The interview question evaluates metric selection, experiment design, int...
Compare Shop and Web Ad Performance Without Overclaiming
Compare Shop and Web Ad Performance Without Overclaiming You have 28 days of daily ad data: `text ads_detail(advertiser_id, ad_id, ad_type, ad_objecti...
Measure Local News Launch Success
This question evaluates experimentation design, causal inference, metric definition, and the handling of interference and selection bias in product an...
Design a causal evaluation without A/B testing
Non-Randomized Launch Decision via Synthetic Control: Complete Analysis Plan You need to make a go/no-go decision for a high-impact feature that canno...
Estimate impact of global launch without holdout
Causal Lift Plan After a Global Launch Without a Holdout Background A new product feature was launched globally on 2025-05-10, with no control or hold...
Estimate ATE of personalization on streaming
You are given a user-level dataset from an online experiment that randomized personalization (treatment) vs no personalization (control). Assume one r...
How would you test a bike delivery option?
This question evaluates experimental design, causal inference, metrics definition, and marketplace analytics competencies in the context of launching ...
Compute partnership profit and break-even population
Co‑marketing Partnership Economics — 12‑Month Evaluation Setup - Issuer C1 earns 1% of a cardholder’s total card spending (interchange-like revenue). ...
Design Testing Without A/B Experiments
Suppose a product team wants to evaluate a new feature that is intended to improve user engagement and long-term retention, but a clean randomized A/B...
Evaluate a new ranking model
A food-delivery company serves homepage store recommendations with ranking model V1.1. A new model V2.0 adds several new features and may require a di...
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...
Design Product Notification and Autocomplete Experiments
You are interviewing for a Product Data Scientist role at Discord. Answer both product experimentation case studies below. Case 1: Subscription notifi...