Reddit Interview Questions
Practice 35 real Reddit interview questions for 2026. Covers all top categories — coding & algorithms, ML and system design, analytics & experimentation, and behavioral leadership — across Software Engineer, Machine Learning Engineer, and Data Scientist roles. Real interview questions from actual interviews with detailed solutions; use this guide for interview preparation so you can target the exact skills Reddit evaluates. Expect a coding-and-systems-heavy loop: Software Engineer questions concentrate on merging message context windows, scalable game leaderboards, sliding-window rate limiters, feature-store CI/CD and reliability, comment-likelihood prediction platforms, and small competitive string/sequence puzzles. Machine Learning Engineer problems mix onboarding and recommendation-system design (comment ranking, video recs), click-prediction modeling, data-loading/JSON edge cases, and short algorithmic tasks. Data Scientist prompts emphasize A/B and non-experimental causal evaluation for ads and chat features (including synthetic-control reasoning), experiment design and power, SQL on US-based users and active forums, probability/estimation puzzles, prioritization, and communicating risk to PMs and engineers. Prep by drilling timed coding, system-design tradeoffs, experiment design and causal frameworks, SQL windowing and performance, production-model evaluation, and clear STAR stories for leadership questions.
"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."
Collaborate with PM and Eng as DS
Question As a Data Scientist working with Product Managers and Engineers: 1. How do you structure collaboration (requirements, timelines, ownership)? ...
Design experiment for ads in chat with budgets
This question evaluates a data scientist's skills in experimental design, causal inference, metrics selection, and handling allocation constraints for...
Prioritize competing engineering requests
Scenario You are a Data Scientist/Analytics partner supporting multiple engineering teams. Two (or more) teams simultaneously ask you to prioritize th...
Justify synthetic control and handle inference
Synthetic Control: Assumptions, Estimation, Inference, and Diagnostics Context You are estimating the causal effect of an intervention on a single tre...
Design a game leaderboard service
This question evaluates a candidate's ability to design scalable, low-latency backend systems and distributed data architectures, covering competencie...
Compute P(A>B) for m- and n-sided dice
Two fair dice are rolled independently: - Die A has m faces labeled \(1,2,\dots,m\). - Die B has n faces labeled \(1,2,\dots,n\). Each face is equally...
Communicate and de-risk a non-experimental launch
Decision-to-Launch Plan After a Synthetic Control Result Context You are a data scientist who used a Synthetic Control method to estimate the causal i...
Measure impact of ads-manager automation feature
This question evaluates competency in causal impact measurement, experimental design, metric selection, monitoring instrumentation, and bias identific...
Build and evaluate click prediction models
Click-Through Rate (CTR) Prediction: Build, Compare, and Justify Models Context You are given a tabular dataset for binary click prediction (click = 1...
Implement a simplified memcached server
This question evaluates a candidate's ability to implement a TCP-based in-memory key-value store, exercising skills in network I/O, protocol parsing, ...
Design a feature store with CI/CD and reliability
System Design: Feature Store for Offline Training and Low‑Latency Online Inference Context You are designing a feature store to support machine learni...
Solve palindrome and list tasks
This question evaluates proficiency in string algorithms and linked list manipulation, specifically techniques for constructing the shortest palindrom...
Implement a sliding-window rate limiter
Problem Design and implement an in-memory rate limiter using a sliding time window. You are given a stream of requests. Each request has: - key (e.g.,...
Load and prepare JSON for modeling
Using Python in a Jupyter notebook, load a JSON dataset with fields: ( 1) hours spent reading A posts (float), ( 2) hours spent reading B posts (float...
Find word sequence with 1–2 char changes
Given a beginWord, an endWord, and a dictionary (wordList) of unique same-length lowercase words, determine whether there exists a transformation sequ...