Senior+ Data Scientist Interview Questions
Senior+ data scientist interviews go deep on experimentation and inference, not just SQL and modeling basics. These questions were reported by candidates interviewing for senior+ DS roles, so they reflect what senior+ loops actually push on: A/B test design and analysis, causal inference when you can't run a clean experiment, metric definition and ownership, and the product judgment to turn an analysis into a decision. At the senior+ level interviewers also probe how you think about ML systems end to end — framing, evaluation, and the trade-offs behind a model in production — and how you influence stakeholders with a result. There are 70+ real, recently reported senior+ data scientist questions here across experimentation, statistics, SQL, ML, and case rounds. Most come with a detailed solution or strong-answer guidance so you can calibrate to the senior+ bar.

"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."
Review Preprocessing Code and Tests
This question evaluates a candidate's competency in data-science engineering tasks including code review, data preprocessing techniques (outlier handl...
How would you evaluate UberEats growth?
This question evaluates product analytics, experimentation design, and causal inference competencies in the context of a food-delivery marketplace, em...
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...
Implement bootstrap mean and variance
This question evaluates a candidate's ability to implement bootstrap resampling and compute statistical estimates for the sampling distribution of the...
Implement bootstrap mean and variance
This question evaluates the ability to implement bootstrap resampling and compute descriptive statistics, testing competency in statistical estimation...
Transform event logs with subscription windows in pandas
Using pandas, compute user-level subscription-aligned revenue and anomalies for September 2025. DataFrames: events(user_id:int, ts:UTC datetime, event...
Implement list overlap and dense-ranked word frequencies
Part A — Multiset overlap count Implement count_overlap(a: List[int], b: List[int]) -> int that returns the size of the multiset intersection of a and...
How would you A/B test first trade rate?
Coinbase wants to increase the rate at which newly signed-up retail users place their first trade. Design an A/B test for a product change intended to...
Design experiment and analyze volume drop scenario
Design an activation experiment for first-trade rate and investigate a retail trading volume drop despite higher BTC volatility. The solution covers A...