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."
Define and analyze new-vs-existing activity
Ambiguous product question: Are existing users more active than new users over the last 28 days (ending today = 2025-09-01)? 1) Propose two reasonable...
Compute churn and revenue churn in SQL
You receive monthly end-of-month subscription snapshots and must compute August-2025 churn metrics. Schema and sample data: Table: subscription_monthl...
Compute churn metrics and rank top students
You have two tasks. Part A (R): You receive a Customers CSV with columns: id (INT), signup_date (YYYY-MM-DD), last_active_date (YYYY-MM-DD), churned (...
Compute browsing metrics in Python from logs
Given event logs, write idiomatic Pandas to compute segment-level metrics and a funnel. Data schema: events(event_id, ts_utc, guest_id, device in {des...
Process real-time enter/exit events and actives
You receive a real-time stream of events with schema: user_id (str), channel (str), event_type ("enter"|"exit"), ts (UTC ISO timestamp). A user can ‘e...
Compute view prevalence from views and labels
Given the tables below, write SQL to compute view prevalence of violating content. Use “today” = 2025-09-01 and report the last 7 days (2025-08-26 to ...
Transform DataFrame and compute diff-in-diff
You are given a pandas DataFrame df with the following columns: - unit_id (string): entity identifier (e.g., user, city, driver) - group (string): eit...
Count Recent High-Volume Call Users
This question evaluates SQL data manipulation and analytical querying skills, including time-window filtering, joins between user and call tables, rol...
Analyze Document Collaboration CSVs
Analyze Document Collaboration CSVs evaluates SQL or pandas logic, joins, grouping, window functions, null handling, edge cases, and validation in a r...
Compute Ride Metrics in SQL
You are given two tables for a ride-hailing product. Tables: - users: one row per registered user. - user_id BIGINT PRIMARY KEY - city VARCHAR NOT...
Find Top-5 Similar Rows
This question evaluates pairwise similarity matching, numerical feature comparison using mean squared error, null-value exclusion, and deterministic t...
Compute Moderation View Metrics
Question You are working on a content moderation analytics problem. You have two tables. Table 1: content_views (one row per user / post / day) - user...
Compute DAU and rolling MAU with zero days
You have two tables in PostgreSQL: Tables users - user_id (STRING / INT, PK) - signup_date (DATE) logins - user_id (STRING / INT, FK → users.user_id) ...
Identify Session with Maximum Overlapping Sessions Count
sessions | session_id | start_time | end_time | | 1 | 2023-01-01 09:00:00 | 2023-01-01 10:00:00 | | 2 | 2023-0...
Calculate User Deviation from Team Average Messages
usage_stats +---------+---------+---------------+------------+ | user_id | team_id | messages_sent | date | +---------+---------+---------------...
Identify Top-3 Users by Recent Total Spend
Users +----+-------+-------------+ | id | name | joined_date | +----+-------+-------------+ | 1 | Alice | 2023-01-02 | | 2 | Bob | 2023-02-14 |...
Convert multi-currency revenue to USD totals
This question evaluates a candidate's competency in converting multi-currency revenue into USD totals by aligning event dates with FX rates, handling ...
Implement Left Join Using Python Dictionaries Efficiently
Orders +---------+----------+--------+ | order_id| customer | amount | +---------+----------+--------+ | 101 | C1 | 250 | | 102 | ...
Write left-join queries with tricky filters
Assume 'today' = '2025-09-01'. Do NOT use window functions (e.g., RANK). Use LEFT JOIN, COUNT(DISTINCT), GROUP BY, HAVING as appropriate. Schema: - us...
Detect sessions and gaps using SQL LEAD
Write a single ANSI-SQL query that (a) assigns per-user session_ids when the gap between consecutive events exceeds 30 minutes, (b) computes session_s...