Uber Interview Questions — Page 52

Uber·Technical Program Manager·Onsite - Product Sense / Strategy

Jun 2026

Product strategy interview for a TPM role at Uber. The main case was a deep competitive comparison between Uber Eats and DoorDash across multiple stakeholder segments, with follow-ups pushing on metrics and tradeoffs. Dense question, lots of moving parts.

Compare Uber Eats and DoorDash from a product and market strategy perspective. Which platform is better positioned, for which user segments, and why?
If you were advising Uber, what should it prioritize next in the food delivery space?
How would you measure whether cross-sell from rides to Eats is actually working?
What would your strategy look like in a city where DoorDash already has stronger restaurant density than Uber Eats?
Which user segment should Uber prioritize first, and how would your answer change if contribution margin is the primary goal?

“This is a monster of a question and I did not scope it fast enough.”

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Uber·Data Scientist·Technical Phone Screen

Jun 2026

Uber DS interview that went deep into experimentation design for a two-sided marketplace. The whole session was basically one long question about switchback experiments, and it got technical fast.

Design an experiment to measure the causal effect of showing different ETAs on whether a rider session ends in a completed ride request. Walk through why a standard A/B test doesn't work here, and propose an alternative experimental design.

“This took me a while to get through cleanly.”

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Uber·Software Engineer·Onsite - Coding / Algorithms

Jun 2026

Uber coding round, graph problem that looks straightforward until you realize cycles are the whole point. Walked away feeling okay about it but not great.

Given a directed graph, find all nodes from which every possible path eventually leads to a terminal node (a node with no outgoing edges). Return a sorted list of all such 'safe' nodes, including the terminal nodes themselves.

“My first instinct was just DFS and mark visited nodes, which completely falls apart once you think about cycles for more than thirty seconds.”

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Uber·Software Engineer·Technical Phone Screen

Jun 2026

Uber phone screen for a SWE role, pretty much centered on the islands problem family. Nothing shocking but the streaming follow-up caught me more off guard than I expected.

Given a 2D grid of '1' (land) and '0' (water) cells, count the number of islands where an island is a group of land cells connected horizontally or vertically.
Follow-up: the grid is too large to fit in memory. How would you handle that?
Streaming variant: starting from an empty grid, you receive a sequence of addLand operations. After each operation, return the current island count.
Additional follow-up: after each addLand operation, also return the size of the largest island at that point.

“Went with DFS immediately, which was fine, but they pushed back and asked if I could do it with union-find instead.”

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Uber·Data Scientist·Technical Phone Screen

Jun 2026

Uber DS interview with a deep experiment design question about promo allocation. The whole session was basically one long case that kept branching into more and more technical sub-problems. Felt like a lot to hold in your head at once.

Design a controlled experiment to test whether a new model (M1) outperforms the existing model (M0) for targeting $5 promotional offers to users.
How would you define the primary success metric for this experiment, and what guardrail metrics would you put in place?
Walk through the sample size calculation for this experiment given a 3% baseline redemption rate, a 0.5 percentage point minimum detectable effect, alpha of 0.05 two-sided, and 80% power.
What analysis approach would you use, and how would you handle variance reduction and repeated looks at the data during the experiment?
How would you handle interference between users or channel saturation in this experiment, and what alternative designs would you consider?
How would you ensure budget parity between experiment arms over time, and how do you handle throttling, suppression lists, and spillover?

“This was the core question and it sprawled in every direction.”

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Uber·Software Engineer·Hiring Manager Screen

Jun 2026

Hiring manager round at Uber for a software engineering role. The conversation felt pretty natural but I came out of it wishing I'd prepped my project narrative way better instead of assuming I could just wing it.

Walk me through the most complex project you've worked on at your current company.
How would you design that same project at a high level if you were starting from scratch?
Tell me about a time you had a conflict with a teammate or stakeholder and how you handled it.

“This is where things went sideways for me.”

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Uber·Product Manager·Onsite - Product Sense / Strategy

Jun 2026

PM interview at Uber, product sense round focused on designing a ride service for kids in India. Pretty niche scenario but actually a fun one to think through.

Uber wants to launch a ride service for children aged 8 to 12 in India. Kids in this age group typically don't have their own phones. What factors would you consider, and what changes would you make to the rider app experience?

“The no-phone constraint is where I should have spent more time upfront but kind of glossed over it and jumped straight into feature ideas.”

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Uber·Product Manager·Onsite - Product Sense / Strategy

Jun 2026

PM interview at Uber, single question about measuring the success of changes to their referral system. Pretty focused session, felt more like a product analytics deep dive than a broad product sense round.

How would you measure whether improvements to Uber's referral program are actually working?

“I jumped straight to activation rate and referral conversion and the interviewer kind of waited for more.”

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Uber·Software Engineer·Technical Phone Screen

Jun 2026

Uber SWE interview, coding round. One LeetCode problem with a bunch of follow-ups that honestly pushed harder than the coding itself. The system design angle caught me more off guard than the binary search part did.

Design a time-based key-value store that supports storing multiple values per key at different timestamps and retrieving the value at the most recent timestamp that doesn't exceed a given query timestamp.
How would you scale this system to handle over a million requests per second?
How do you ensure thread safety in this data structure, and what are the trade-offs between different locking strategies?

“Got the structure right pretty fast, per-key list with binary search on get.”

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Uber·Software Engineer·Technical Phone Screen

Jun 2026

Uber coding screen for a software engineer role, one algorithmic question the whole time. Pretty standard session, nothing fancy about the setup.

Given an array of item prices, return the final price of each item after applying a special discount rule: for each item, find the first later item whose price is less than or equal to the current item's price and subtract it as a discount. If no such item exists, the price stays the same.

“I recognized this was a stack problem pretty fast, which felt good.”

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