Data Scientist Interview Questions
Practice 2,964 real Data Scientist interview questions for 2026. Data Scientist interview questions drawn from Meta, Capital One, Amazon, Google, TikTok and similar employers — real questions from actual interviews with detailed solutions — designed to accelerate your interview preparation for product analytics, ML and production data roles. This collection emphasizes the practical skills interviewers test: SQL and data manipulation, experiment design and A/B testing, statistical reasoning, Python coding for data problems, model evaluation and feature engineering, plus machine-learning system tradeoffs and metric design. What’s distinctive about modern data-science loops is the blend of product thinking and reproducible ML: expect hands-on SQL tasks and funnel analysis in screens, deeper experiment-design and causality questions in mid rounds, and coding or modeling challenges plus ML-system discussions in senior loops. Interviewers evaluate problem framing, statistical rigor, and how you communicate decisions to product partners. To prepare, prioritize daily SQL practice (CTEs, window functions), refresh hypothesis-testing and power calculations, rehearse concise metric-driven narratives, and build a few end-to-end model or experiment stories you can explain clearly under time pressure.
"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."
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"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."
Stabilize LLM inference and estimate needed repeats
You run an LLM-based sentiment model to score a fixed dataset of texts. Because the inference API doesn’t let you set temperature (and outputs are sto...
Compute probability last passenger gets own seat
There are 100 passengers boarding a plane with 100 seats, numbered 1 to 100. Passenger i (for 1 ≤ i ≤ 100) has a ticket for seat i. The boarding proce...
Evaluate Top-Dasher Program's Benefits and Challenges
Scenario DoorDash is considering several driver-facing initiatives: a Top-Dasher status, cash incentives, and a tiered rewards program. Questions 1) T...
Estimate Treatment Effects Using PSM, DiD, and DML Methods
Causal Impact of Marketing Campaigns: PSM, DiD, Synthetic Control, and DML Scenario You have observational data from a marketing campaign where some u...
Identify Overlapping Sessions and Optimize Coverage
Scenario During the technical screen, candidates must implement interval algorithms used in fraud-detection pipelines to reconcile overlapping user ac...
Determine Revenue and Cost Components for Credit-Card Issuer
Credit-Card Issuer Unit Economics and Break-even Analysis Scenario A card issuer is considering launching a new 1% cashback card alongside its existin...
Analyze Rider Behavior in Dynamic-Pricing Trial
Dynamic-pricing trial: rider behavior Context (assumptions made explicit) - Each day the rider has two potential ride opportunities. - For any specifi...
Estimate Revenue and Profitability for Share Workplace's Paid Tier
Freemium + Subscription Sizing, Margins, and Marketing Impact (Year 3) Context You are evaluating a freemium enterprise collaboration app ("Share Work...
Calculate Probability and Statistics for Dice Roll Outcomes
Dice Rolls and the Binomial Model Scenario A casino analyst models dice rolls to understand outcome probabilities for marketing promotions. Question Y...
Explain Statistical Outputs to Non-Technical Stakeholders
A/B Test Dashboard Interpretation and Core Statistics Concepts Scenario You are reviewing an A/B test dashboard for an experiment (e.g., Variant B vs ...
Design A/B Test for Cost-Per-Conversion Efficiency Analysis
Multi-Arm A/B Test: Comparing Cost-Per-Conversion Across Channels Scenario You need to compare four new acquisition channels—YouTube ads, Google Searc...
Determine Rent Price Factors for Multi-Family Apartment Profitability
Apartment Pricing and Break-even Analysis (100 Units) Context You are evaluating rent pricing for a 100-unit multifamily building. Assume the followin...
Navigate Conflicting Priorities in Cross-Functional Collaboration
Behavioral Interview: Cross-Functional Collaboration, Trade-offs, and Working Style Context You are interviewing for a Data Scientist role in a techni...
Identify Pirate Themes Using Similarity Score Algorithm
Scenario Engineering wants an automated way to spot custom themes that are probably just pirate themes in disguise. Question Write Python that takes t...
Implement sparse vector dot product and cosine similarity
Sparse Vector Class Implement a SparseVector class for high-dimensional vectors where most entries are zero. Representation Assume each vector has: - ...
Handle feedback, change pivots, and conflict
Question In the behavioral portion of the Meta Data Scientist screen, answer the following leadership prompts using concrete examples from your own wo...
Investigate why an advertiser’s spend decreased
A video ads product has two ad formats: - Direct ads (optimize for in-platform actions) - Brand ads (user clicks the video and lands on the advertiser...
Compare performance of FB vs IG Stories
You are asked to compare ads performance between two placements/products (e.g., Facebook Stories vs Instagram Stories) and make a recommendation on wh...
Handle imbalance, sampling, and overfitting
Practical ML questions (classification and generalization) Answer the following ML engineering/data science questions. A) Class imbalance You’re train...
Compute ads revenue by geography in SQL
You have ad delivery logs for a shop-ads system. Tables ad_impressions - impression_id STRING (PK) - ts TIMESTAMP (UTC) - user_id STRING - shop_id STR...