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."
Design an unsafe content detection system
This question evaluates a candidate's competency in end-to-end machine learning system design for unsafe user-generated content detection, covering mu...
Design a Google Photos–like service
System Design: Google Photos–like Service (Web + Mobile) Context Design a large-scale consumer media service that ingests, stores, indexes, and serves...
Demonstrate culture fit with examples
Behavioral & Leadership Interview (Software Engineer Onsite) You are preparing for an onsite behavioral and leadership interview for a Software Engine...
Explain bias–variance, overfitting, and vanishing gradients
This question evaluates understanding of core machine learning fundamentals—specifically the bias–variance tradeoff, overfitting detection and mitigat...
Design highly available blob storage service
Design a large-scale, highly available blob storage service similar to Amazon S3. The service should allow clients to store, retrieve, and delete arbi...
Design autocomplete and merchant bulk edits
This question evaluates a candidate's system design competency across real-time search/autocomplete and large-scale product update pipelines, covering...
Build an emoji blaster animation on iOS
iOS "Blaster" App: Press-and-Hold Emoji Projectiles Problem Build a minimal iOS app with a button fixed at the bottom. While the user presses and hold...
Design Pin recommendation system
Design Pinterest's Home Feed Recommendation System Problem Design an end-to-end recommendation system that powers the personalized home feed on Pinter...
Maximize Boxes Stored Through One Entrance
This question evaluates array manipulation, constraint reasoning, and optimization skills, touching on greedy and combinatorial allocation concepts un...
Decide if ad load is optimized
Pinterest Home Feed Ad Load Optimization You are asked to design an analysis and experiment to determine whether the current home-feed ad load (ads pe...
Explain learning-rate fluctuation and vanishing gradients
ML Fundamentals Answer the following conceptual questions: 1. Learning rate vs. training stability: Why can training metrics (loss/accuracy) fluctuate...
Demonstrate leadership with concrete STAR examples
Behavioral & Leadership (Onsite) — STAR Examples With Metrics Provide succinct STAR-format examples (Situation, Task, Action, Result), with specific m...
Recover causal effect without a control group
Post-hoc Causal Estimation After a Failed A/B Rollout Context An intern accidentally shipped a feature to 100% of eligible users for 5 consecutive day...
Estimate Highway Billboard Impressions Using Traffic Data
Estimating Highway Billboard Reach and Impressions An out-of-home advertising team wants to estimate reach and impressions for a single highway billbo...
Design an ads system to improve CTR
Design an ML system to increase the click-through rate (CTR) of ads shown in the personalized feed of an online social media platform. You run the ran...
Design and Evaluate a Home Carousel
Pinterest is considering adding a horizontally scrollable carousel at the top of the Home feed, similar to Instagram Stories. The carousel may surface...
Design rigorous A/B test and causal analysis
Experiment Design and Causal Inference: Multi-part Problem Context: You are designing a high-traffic web A/B test on a binary conversion metric. Answe...
Analyze survey with gender imbalance
Analyze survey with gender imbalance Scenario You ran a user survey to measure satisfaction with a new product feature. Each respondent reports: - gen...
First Word Matching Each Prefix Query
This question evaluates a candidate's grasp of string data structures and efficient prefix-matching techniques, core competencies in coding and algori...
Mark and Compact a Heap-Indexed Subtree
Mark and Compact a Heap-Indexed Subtree An interview report describes an array-encoded tree, marking a target and its descendants with -1, then moving...