Thumbtack Interview Questions
Practice the exact questions companies are asking right now.
"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."
"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."
Lead XFN decision under tight timeline
Scenario: 72-Hour VP-Level Recommendation on Expanding a New Quoting Workflow You have 72 hours to deliver a VP-level deck recommending whether to exp...
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...
Optimize red-ball draw probability, prove optimality
Two-Box Ball Allocation to Maximize Probability of Drawing Red Setup - You have 2 boxes and two colors of balls. - In the 100/100 case: 100 red and 10...
Detail NLP preprocessing and n‑gram choices
Describe your text preprocessing pipeline given the source modality: typed text, scanned/handwritten OCR, or speech-to-text. Specify language handling...
Compare list/dict; parse JSON/CSV at scale
Compare Python list and dict precisely: for append/insert/lookup/update/delete, state average and worst-case time complexity, memory implications, and...
Demonstrate rapid analysis and stakeholder debrief
Rapid Analysis and Stakeholder Debrief Plan You have 1 hour to analyze a provided dataset (no pre-read) followed by a 45-minute debrief with a product...
Present a DS project with business impact
7-Minute Data Science Project Presentation (Onsite) Context You are interviewing for a Data Scientist role and will present a past project to a mixed ...
Design cross-validation; explain bias–variance
Define cross-validation rigorously and compare k-fold, stratified k-fold, leave-one-out, nested CV, and time-series rolling/blocked CV. For a dataset ...
Choose clustering vs regression; explain KNN
When would you use clustering vs. regression on a business problem with partially labeled outcomes? Specify the decision criteria (label availability,...
Explain power drivers and resolve unexpected A/B results
A/B Testing: Power, Sample Size, Allocation, and Diagnostics You are analyzing a two-proportion (binary conversion) A/B test with independent users, n...
Design and evaluate an A/B test for launch
A/B Test Design: New Matching Model for a Two‑Sided Marketplace Context You are testing a new matching/ranking model that determines which providers a...
Forecast response-rate trends with backtesting
Forecasting Response Rate by Job Category and Week Context You are given weekly marketplace data with invitations and responses by job_category and re...
Define success metrics for Instant Book
Instant Book: Metrics, Measurement, Rollout, and Risk Plan Context You are evaluating an "Instant Book" feature that allows customers to immediately b...
Implement min, mean, median robustly
Implement three functions in Python without using numpy/pandas: (1) my_min(nums) returning the minimum in O(n) time and O(1) space; (2) my_mean(nums) ...
Explain a project and justify choices
Walk me through your most impactful project end-to-end: what problem and success metric did you define, what alternatives did you evaluate and reject,...
Implement TF–IDF with sparse matrices
Implement TF–IDF from Scratch (Python + NumPy/SciPy) You are given a list of documents (strings). Build a TF–IDF vectorizer from scratch with the foll...
Build a defensible ML pipeline end-to-end
End-to-End Binary Classification Pipeline on Tabular Data (Numeric, Categorical, Text) Context You are handed a tabular dataset that includes numerica...
Design streaming new-vs-returning monthly metrics
Streaming design: Monthly NEW vs RETURNING request shares (event-time, with late/out-of-order and duplicates) Context You receive a high-volume event ...
Test regional response-rate differences rigorously
Goal Assess whether provider response rates differ by region after adjusting for job category mix and time. Data You have job-level observations with ...
Write monthly new-vs-returning requests SQL
Given the schema and sample data below, write a single PostgreSQL query (no dynamic SQL) that returns, for every calendar month present in requests, t...