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Yahoo interview notes, page 2 of 2

Large Enterprises

Most of these Yahoo write-ups come from Data Scientists (11), then Machine Learning Engineers (3) and Product Managers (3). The most reported rounds are the technical phone screen (13), the product sense round (4), the behavioral / leadership round (2) and the hiring manager screen (1).

20 interview notes · updated Jul 2026

Yahoo·Machine Learning Engineer·Technical Phone Screen

Jun 2026
Yahoo MLE interview, one round that was basically a structured background walkthrough with a deep technical dive into a past project. Nothing too wild but the level of detail they expected on the project side was more than I anticipated.
  • Walk me through your background and do a deep dive on one specific project you've worked on.

“I underestimated how deep they wanted to go.”

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Yahoo·Data Scientist·Technical Phone Screen

Jun 2026
Data scientist interview at Yahoo, one case-style question about diagnosing a DAU drop in Yahoo Mail. Pretty open-ended, which sounds fine until you're actually sitting there trying to structure your thoughts on the fly.
  • Yahoo Mail's daily active users dropped by 10% suddenly. How would you go about finding the root cause? Walk through what data you'd look at, which segments or funnels you'd dig into, and how you'd figure out whether this is something internal or something external.

“I started with the obvious stuff, platform breakdown, geography, recent releases, and that part felt okay.”

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Yahoo·Data Scientist·Technical Phone Screen

Jun 2026
Got pulled into a probability question mid design review at Yahoo, which I was not expecting from a PM. It was framed as a quick gut check but ended up being more involved than it sounded.
  • You flip a fair coin over and over until you see Heads followed immediately by Tails. How many flips should you expect to need on average?

“I stared at this for a second because it looks like a simple probability problem but it really isn't.”

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Yahoo·Software Engineer·Onsite - Product Sense / Strategy

Jun 2026
Yahoo threw a big open-ended resource allocation question at me and I genuinely wasn't sure if there was a right answer or if they just wanted to see how I think.
  • If you had 20 engineers, 100,000 computers, and 3 months, what would you build?

“Blanked for a solid few seconds on this one.”

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Yahoo·Data Scientist·Technical Phone Screen

Jun 2026
Yahoo Data Scientist interview with a coding question that looked straightforward but had enough constraints layered on top that it took me a minute to get my footing. One question, but they really dug into the details.
  • Write a function that removes duplicates from a list while keeping the order of first appearance, in O(n) time and O(k) space where k is the number of unique elements. It must handle strings case-insensitively but return the original casing of the first occurrence. Then explain the complexity and what breaks if elements are not hashable.

“The case-insensitive part is what tripped me up initially.”

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Yahoo·Data Scientist·Technical Phone Screen

Jul 2026
SQL-heavy Data Scientist screen at Yahoo, five questions all built around a single transactions table. Nothing conceptually wild but the window function stuff got tricky fast and I wasn't as sharp on the revenue drop calculation as I wanted to be.
  • Given a transactions table with user_id, amount, and date columns, write a query that returns each user's total spend rounded to two decimal places.
  • Using the same transactions table, return the user_id(s) with the second-highest total spend.
  • List all users whose number of transactions is greater than the average transaction count across all users.
  • For each date in the table, calculate the percentage drop in revenue compared to the previous day, and return only dates where the drop is 10% or more.
  • For every user, return their first purchase date and the total amount they spent on that specific day.

“Warmup question, pretty much just GROUP BY user_id with SUM and ROUND.”

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Yahoo·Data Scientist·Technical Phone Screen

Jul 2026
Coding round for a Data Scientist role at Yahoo, two Python problems focused on list manipulation. Nothing too wild but the second question had some edge cases that could trip you up if you weren't careful.
  • Given a list of integers, remove all duplicates while keeping the elements in their original order.
  • Given a list of lowercase words, merge them into a single string by overlapping the last character of each word with the first character of the next word whenever they match. For example, ['abc','rgn','ctr'] produces 'abctrgn'. You also need to handle cases where there's no overlap or potentially multiple overlapping characters.

“Pretty standard dedup problem.”

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Yahoo·Data Scientist·Technical Phone Screen

Jul 2026
Yahoo DS interview with a meaty SQL question that took up the whole session. The problem looked like a standard DAU diagnostic but had enough edge cases layered in that I was still untangling things near the end of my time.
  • Write a single SQL query to diagnose a country-level DAU drop for an email product. Compare DAU on 2025-09-01 to the average DAU over the prior 7 days (2025-08-25 through 2025-08-31). Exclude bot events and users in the treatment arm of an active experiment. Output the top 3 countries by absolute DAU drop with columns for country, 7-day average DAU, today's DAU, absolute drop, and percent drop. Also break out today's DAU into returning vs new users. Break ties by larger drop percent.

“The experiment exclusion tripped me up more than I expected.”

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Yahoo·Data Scientist·Hiring Manager Screen

Jul 2026
Interviewed for a Data Scientist role on the business intelligence side at Yahoo. The round was mostly behavioral, centered on motivation and how you work with people outside your immediate team. Nothing technically brutal, but the communication question had more depth to it than I expected.
  • Why do you want to join Yahoo and this specific role on the business intelligence team?
  • Where do you see your career going over the next few years?
  • Tell me about a time you had to explain a complex technical concept to people without a technical background. How did you make sure they actually understood and were on board?

“I had a decent answer prepped but it felt a little rehearsed coming out.”

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Yahoo·Data Scientist·Technical Phone Screen

Jul 2026
Yahoo data science interview with a gaming analytics team that threw a probability puzzle at me I genuinely was not expecting. The question was more math-heavy than I anticipated for a DS role, felt like it belonged in a combinatorics class.
  • You have two standard six-sided dice. Is it possible to relabel the faces so that when you roll both, every sum from 1 to 12 comes up with equal probability? Either show how you'd do it, or prove it's impossible.

“I stared at this for way too long before saying anything useful.”

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