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."
Design an online coding contest platform
This question evaluates a candidate's ability to design scalable, reliable, and secure distributed systems for real-time, event-driven workloads, cove...
Build an end-to-end ML pipeline
Build an end-to-end ML pipeline ML System Design: Shipment Delay Risk Scoring From a Single CSV You are given a CSV of shipment events with the follow...
Design a ticketing purchase system
System Design: High-Concurrency Ticket Purchasing With Seat Maps You are asked to design an end-to-end ticketing system for large on-sale events (e.g....
Handle deadlines and misses
Handle deadlines and misses This is a two-part behavioral question. Answer both parts: 1. Tight deadline. Describe a time you faced a tight deadline. ...
Describe conflict resolution, prioritization, and collaboration
Describe conflict resolution, prioritization, and collaboration Behavioral Prompt: Conflict Resolution and Leadership (Software Engineer, Onsite) Inst...
Explain surprisal and its units
You are discussing a language-modeling / NLP project. The interviewer asks about surprisal. 1. Define surprisal for an event/token with probability \(...
How would you analyze and test a price increase?
Case Study (Product / Data Science) You work on a subscription-based AI video editing/creation product and leadership is considering raising prices (e...
Evaluating a 15 % reduction in post‑card height
Evaluating a 15 Percent Reduction in Post-card Height You own the feed UX for a social app. Designers propose shrinking each post card's height by 15 ...
Compare Ad-Insertion Strategies: Expected Ads and Probabilities
Newsfeed Ad-Insertion Strategies You are evaluating two ways to insert ads into a user's newsfeed. A user views a contiguous sequence of posts. - Stra...
Fake Accounts [AE]
Evaluates probability, classification metrics, and feature engineering for fake-account detection. Strong answers apply Bayes' rule with rate-weighted...
Describe Handling Cross-Functional Projects and Changing Priorities
Describe Handling Cross-Functional Projects and Changing Priorities This behavioral prompt evaluates how you collaborate across functions, respond to ...
Compute ad revenue metrics by geography in SQL
You work on a marketplace app that shows shop ads. You are given the following tables. Assumptions - All timestamps are stored in UTC. - “Revenue” is ...
Compute sample size and test duration
You will run a two-arm A/B test on a signup funnel. Given: baseline conversion p0 = 4.0%; you care about detecting a 10% relative uplift (p1 = 4.4%); ...
Find companies similar to a given client
System Design: Retrieve Top-20 Most Similar Companies for Sales Prospecting You are given an anchor client (e.g., The Coca‑Cola Company). Design a sys...
Diagnose 10–11% usage drop across geos
US usage is down 10% and Mexico is down 11%. List plausible confounders (seasonality, pricing, outages, marketing mix, competitor moves, feature rollo...
Demonstrate Amazon LP with deep follow-ups
Behavioral STAR Stories for Amazon Data Scientist Onsite Context You are preparing for an onsite Behavioral and Leadership interview for a Data Scient...
Design video-ads experiment and handle null results
You are launching a new video-ad format. Design an end-to-end A/B test to evaluate it against the current ad format. Be precise: 1) Define exposure an...
Decide standardization, sparse numerics, correlated features
You are given a tabular dataset for supervised learning with features: F1 (counts, mostly small integers with many zeros), F2 (monetary amounts in dol...
Handle highly imbalanced classification data
You must build a binary classifier for fraud with a 0.2% positive rate and 10M rows × 500 features. Propose an end-to-end plan that covers: 1) data sp...
Explain linear regression to non‑technical stakeholders
This question evaluates understanding of linear regression fundamentals and related competencies, including defining target, features, coefficients, i...