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."
Write SQL for top student per department
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Implement left join on Python lists, no packages
Implement a left join in pure Python (no external packages, no pandas). Input: left = list of dicts with key 'id' and arbitrary other fields; right = ...
Compute CTR overall and by campaign type
Write SQL to compute: (Q1) overall click-through rate (CTR = clicks/impressions) in the last week; (Q2) CTR by campaign_type in the last week. Assume ...
Find most co‑purchased product pairs in SQL
Given the schema and sample data below, write ANSI-SQL to return the top 5 unordered product pairs most frequently purchased together across distinct ...
Design a scalable video platform database
Design the relational database for a YouTube-like video company. Deliverables: 1) list the core tables with key columns, types, and constraints (users...
Write SQL for percent and window changes
Use PostgreSQL. Assume today = 2025-09-01. You must use CTEs and multiple window functions. Schema and tiny samples are below. Schema: - exposures(uni...
Merge four CSVs locally, robustly and efficiently
You receive four CSV files that must be merged locally on a laptop with 8 GB RAM, without relying on cloud services: - products.csv: product_id, categ...
Write SQL for lowest price with ratings
You have two tables. Schema: - products(product_id INT PRIMARY KEY, product_name TEXT, category TEXT) - purchase(purchase_id INT PRIMARY KEY, product_...
Transform messy transactions with pandas
You are given two CSVs. transactions.csv - Columns: txn_id, user_id, ts_iso (ISO8601 with timezone), amount (decimal USD; refunds negative), merchant_...
Analyze shopping funnel with joins and windows
Write SQL (PostgreSQL) to analyze a 4-step shopping funnel: view_product → add_to_cart → checkout_start → purchase. Use the schema and sample data bel...
Compute C/T metrics from bookings and visits
Given two tables, compute control vs treatment (C/T) metrics, apply 24‑hour attribution, and generate a daily plot. Treat “today” as 2025‑09‑01; use t...
Unify 7 tables and impute missing values
Using pandas, write a robust function unify_orders(...) that ingests seven dataframes (or CSVs) with possibly inconsistent column casing/whitespace an...
Calculate annual percentages and YoY by cohorts
Answer both SQL and Python parts. Be precise about deduping and denominator choices. SQL schema (sample rows): orders order_id | user_id | order_date ...
Design SQL/Pandas aggregations on retail schema
Using the schema and sample data below, answer both parts. Assume today is 2025-09-01. Use standard SQL (e.g., PostgreSQL) and idiomatic pandas withou...
Find top video category by average time
You are given a pandas DataFrame 'pins' with columns [pin_id:int, category_id:int, time_spent_sec:float, pin_format:string] and a dict 'category_map' ...
Compute multi-account actives and unread coverage
You have two tables. Table: notifications +--------+------------+------------+-------------------+--------+ | userid | ds | time | notification_type |...
Compute violation rate and flag precision in SQL
You are analyzing a Trust & Safety product in BigQuery. Assume 'today' is 2025-09-01 (UTC). Define precise metrics and write SQL to compute them, bein...
Write SQL for TikTok Live creator metrics
You are analyzing TikTok Live sessions and their engagement. Tables live_room Each row is a Live session (“room”) launched by a creator. | column | ty...
Find high-value crypto users and top-CTR product
You are given three tables (timezone: UTC). Assume create_date, transaction_time, and event_time are timestamps. Tables users - user_id BIGINT PRIMARY...
Compute each member’s current notification status
Question You are given two tables describing LinkedIn members’ push-notification settings. Compute each member’s current notification status as of 202...