Meta + Google + TikTok + Amazon Interview Questions
Practice the exact questions companies are asking right now.
"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."
Compute monthly CRR with merges and gaps
You are given PostgreSQL tables user_profile(user_id, signup_ts, country, is_employee, is_test), user_events(user_id, event_ts, event_type, revenue, p...
Compute survey rates and bias-correct ratings
Today is 2025-09-01. Use the schema and sample data below to answer A and B with SQL (standard SQL; you may use CTEs and window functions). Assume tim...
Write SQL to localize anomaly and funnel
Given the schema and toy data below, write SQL to (a) validate instrumentation vs behavior change, (b) localize the 2025-09-01 Likes drop by app_versi...
Model preference without ground truth
This question evaluates a data scientist's competency in uplift modeling, causal inference, experimental design, weak supervision, and bias and shift ...
Verify subscriptions and analyze orders with SQL/Python
You are given two tables. Write SQL and Python (pandas) to answer the sub-questions precisely, handling edge cases, ties, and missing data. Schema - s...
Model overdispersed counts; estimate treatment lift
This question evaluates modeling and inference for overdispersed, zero‑inflated count data, including estimation of treatment lift (rate ratios), disp...
Design experiment with network and novelty effects
This question evaluates a data scientist's competence in experimental design and causal inference under network interference and novelty effects, cove...
Define success metrics beyond time spent
This question evaluates a data scientist's competency in product analytics and experimentation, focusing on metrics design, cohort-based retention mea...
Implement randomized Quickselect without k-shift bug
Implement randomized Quickselect to return the k-th largest element (1-based k, 1 ≤ k ≤ n) from an unsorted integer array. Use an in-place partition t...
Compute binary-tree diameter via return-only DFS
Given the root of a binary tree, compute its diameter defined as the number of edges on the longest path between any two nodes. Implement a DFS that r...
Write SQL to analyze Group Calls adoption
Write SQL (assume PostgreSQL) to analyze Group Calls adoption and cannibalization. Use this schema and sample data. Schema: - users(user_id INT PRIMAR...
Compute last-to-previous ad impression gaps
Given impressions(ad_id INT, user_id INT, impression_ts TIMESTAMP) with multiple impressions per (user_id, ad_id), write a single SQL query to return,...
Measure Ads Manager effectiveness end-to-end
This question evaluates a candidate's competency in experimental design, causal inference, metric definition, telemetry instrumentation, and heterogen...
Compute CTR drop with exclusions
Assume today = 2025-09-01. Using ad delivery logs, find advertisers whose CTR in the last 7 days (2025-08-25 to 2025-08-31) dropped by at least 20% re...
Design experiments and observational alternatives
This question evaluates causal inference, experimental design, metric definition and measurement, power analysis, segmentation, and observational stud...
Define and analyze new-vs-existing activity
Ambiguous product question: Are existing users more active than new users over the last 28 days (ending today = 2025-09-01)? 1) Propose two reasonable...
Compute and correct correlation significance inflation
This question evaluates statistical inference for correlations, multiple testing control (false discovery rate), power and sample-size calculations, a...
Identify latent group-call demand from behavior
This question evaluates a data scientist's ability to design measurable product-analytics signals, infer latent user demand from event-level messaging...
Design fraud detection across channels with unknowns
This question evaluates a data scientist's competence in designing and operationalizing multi-channel fraud detection systems, covering cost-sensitive...
Design and justify unread-account pinning experiment
This question evaluates a data scientist's competency in experimental design, causal inference, metric definition, instrumentation, and analysis for p...