Data Scientist Data Manipulation (SQL/Python) Interview Questions
Practice 550 real Data Manipulation (SQL/Python) interview questions for Data Scientist roles. From companies including Meta, Amazon, TikTok, Capital One, DoorDash.
"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."
Build a cohort dashboard with Streamlit and SQL
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Compute last-to-previous ad impression gaps
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Calculate cross-channel login user proportions
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Compute CTR drop with exclusions
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Compare SQL counts, windows, and NULL semantics
You’re given two tables. users(id INT, country STRING, created_at DATE) rows: 1 | US | 2025-08-28 2 | US | 2025-08-30 3 | IN | 2025-08-29 4 | BR | 202...
Write SQL for snapshot features and labels
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Compute 7-day rolling complaint/order ratio in SQL
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Write SQL for comment analytics
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Manipulate data in R with dplyr joins and windows
Using R and dplyr, answer the following using these small tables (dates are ISO strings): transactions(user_id, order_id, order_date, channel, amount)...
Write complex SQL for streaming funnels
You are analyzing a Disney/Hulu product funnel with events captured in a single table. Write ANSI-SQL (Snowflake/BigQuery compatible) to answer the su...
Transform nested dicts with pandas apply/lambda
Given a pandas DataFrame df with columns: user_id (int), ts (datetime64[ns]), events (list of dicts), attrs (dict). Example rows (conceptual): user_id...
Write windowed retention and ARPU SQL
You are given three tables. Write one SQL script (CTEs allowed) that answers all parts using window functions and joins (no procedural loops): Schema:...
Compute leakage-safe rolling features in pandas
Using pandas on a 50M-row monthly panel with columns [loan_id, msa, month, property_type, delinquent_90dpd (0/1), upb], create features for each loan-...
Write advanced SQL for sales support analytics
Write SQL for the following schema and tasks. Assume ANSI SQL with DATE_TRUNC and INTERVAL supported. Sample tables (minimal rows shown). accounts +--...
Audit and onboard unfamiliar datasets safely
You inherit unfamiliar hotel search data with sparse documentation. Provide a concrete, ordered checklist to: a) discover tables/columns and verify pr...
Write SQL/Python for CTR analytics
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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...
Write complex joins and window functions
You are given a simplified Thumbtack-like marketplace schema in PostgreSQL. Assume UTC timestamps and weeks start on Monday. Treat "today" as 2025-09-...
Compute shop visibility and intent metrics in SQL
Schema (PostgreSQL). Tables: users(user_id) shops(shop_id, shop_name, merchant_type) posts(post_id, shop_id, is_shoppable BOOLEAN, created_at TIMESTAM...