Pinterest Interview Questions
Practice 145 real Pinterest interview questions for 2026. Covers all top categories — Coding & Algorithms, Data Manipulation (SQL/Python), Analytics & Experimentation, Machine Learning, System Design — across Data Scientist, Software Engineer, Machine Learning Engineer, and Data Analyst roles. Real questions from actual interviews with detailed solutions. This collection leans hard on coding and algorithm problems for SWE candidates while giving equivalent weight to experiment design, SQL/Python analytics, and model evaluation for data roles, making it a focused resource for interview preparation for screens, virtual onsites, and take-home assignments. Expect interviews to evaluate algorithmic thinking, production design, experimental rigor, and clear data storytelling. For Data Scientists you’ll see carousel and billboard lift evaluation, weighted/random-sampling implementations, numpy/pandas and SQL analytics on category and video-time metrics, and survey-balance diagnostics. Software Engineers face prefix-matching, catalog update pipelines, sparse-matrix ops, grid/graph puzzles, and ads event reporting or blob storage design. Machine Learning Engineers get pin-search and recommender design, Naive Bayes/bagging implementation, hyperparameter generation, and sampling-by-score problems. Data Analysts encounter cohort and cancellation/rebooking metric questions. Prepare with timed coding drills, end-to-end A/B case studies, polished Python/SQL practice, and concise STAR stories for behavioral rounds.
"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."
How would you evaluate a carousel launch?
This question evaluates a data scientist's skills in experimental design, product-metric specification, causal inference, and diagnostic analysis for ...
Collect Pins from Reachable Boards
Collect Pins from Reachable Boards The interview report names a board-and-pin coding problem whose intended approach was breadth-first search but does...
Design an ads event reporting system
This question evaluates a candidate's ability to design scalable, reliable event ingestion and analytics systems, testing competencies in distributed ...
Evaluate Fresh Content and Video Experiments
Pinterest wants to improve the perceived freshness and engagement of the home feed. Answer the following interview questions: 1. Define a practical me...
Implement a Stateful Search Autocomplete Session
Implement a Stateful Search Autocomplete Session Build an autocomplete engine from historical sentences and their usage counts. While a user types a s...
Reconstruct itinerary with lexicographic ties
You are given m airline tickets as directed pairs [from, to]. Build an itinerary that starts at a specified airport start (e.g., "JFK") and uses every...
Explain overfitting, underfitting, and regularization
This question evaluates understanding of model generalization, overfitting versus underfitting, the bias–variance tradeoff, and regularization techniq...
Design Detection Systems for Risk and Safety
This question evaluates a machine learning engineer's competence in designing end-to-end detection systems for risk and safety, covering skills in dat...
Implement bagging with decision trees
Implement a simple bagging (bootstrap aggregating) classifier that uses decision trees as base learners. You are given a template with a DecisionTree ...
Evaluate Carousel and Billboard Lift
This question evaluates experiment design, causal inference, metric definition, diagnostic analysis, and measurement validity within the Analytics & E...
How to evaluate a new Carousel feature
This question evaluates a data scientist's competence in experimentation design, measurement framework formulation, metric definition, and diagnostic ...
Answer core ML fundamentals questions
You are asked several short ML fundamentals questions: 1) Define precision and recall for a binary classifier and explain how they relate to a confusi...
Implement Naive Bayes classifier from scratch
Implement a Naive Bayes classifier from scratch (you may use NumPy). Write a class with: - fit(X, y): estimate class priors and feature likelihood par...
Design a real-time home feed ranker
This question evaluates an engineer's ability to design scalable, low-latency real-time recommendation and ranking systems that integrate personalizat...
Implement tap-to-infect color grid on iOS
iOS Grid Infection (Flood Fill) Design Goal Build an iOS app that displays a 2D grid with two colors. When the user taps a cell, all 4-directionally a...
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...
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 notification and feed recommenders
This question evaluates an engineer's ability to design scalable, production-ready recommendation systems for notifications and home feeds, encompassi...
Explain BLS vs CLS; compute t-stats
Part A — Concepts: Define Brand Lift Study (BLS) vs Conversion Lift Study (CLS) in ads measurement. List key bias/variance sources for each (e.g., non...
Solve a 9x9 Sudoku puzzle
Given a partially filled 9×9 Sudoku board, fill the empty cells so that the completed board is valid. A valid Sudoku satisfies: - Each row contains di...