Roku Interview Questions — Page 1

Roku·Data Scientist·Technical Phone Screen

Jan 2025

Roku DS interview that went deep into causal inference for a hardware launch scenario. Four-part case question, no behavioral stuff from what I remember, just a long technical grind.

For a newly launched smart speaker with voluntary adoption, define a primary engagement metric and the guardrail metrics you'd put around it.
Design two complementary strategies to estimate the causal effect of speaker adoption on engagement at 30 and 180 days, given you can't run a traditional A/B test.
Use regional stockouts and shipping delays as an instrumental variable. Argue why it's a valid instrument and describe how you'd run falsification tests.
Do a rough power calculation given 6% adoption rate and historical variance. What sample size or time horizon would you need to detect a 3% lift in engagement?

“I went with something like daily active streaming minutes per device, which felt right, but I fumbled the guardrail framing.”

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Roku·Software Engineer·Onsite - System Design / Architecture

Apr 2026

System design round at Roku for a software engineer role, focused entirely on designing an ad exchange from scratch. Pretty intense scope for a single session, covering everything from auction mechanics to budget pacing at scale.

Design a real-time ad exchange system that handles auctions between publishers and advertisers at very high throughput with strict latency constraints.
How would you handle bidder timeout and partial bid collection in a real-time auction protocol?
What data model would you use for campaigns, budgets, and targeting filters?
How would you implement budget pacing and frequency capping at scale, given the QPS requirements?
Walk me through the logging pipeline for impression, click, and conversion events and how it feeds downstream analytics.
What storage and caching choices would you make to support low-latency lookups during the auction?

“This is the kind of question where you think you know ad tech until you're actually drawing it out.”

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Roku·Software Engineer·Technical Phone Screen

Apr 2026

Got a coding question at Roku that was pretty much a textbook dynamic programming problem. Not much context about the role or how the round went, but the problem itself was LCS, which is a classic.

Given two strings, find the length of their longest common subsequence. A subsequence keeps characters in order but doesn't require them to be contiguous. Return 0 if none exists.

“Classic DP problem and I knew it, but I still fumbled explaining the recurrence relation out loud.”

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Roku·Data Scientist·Onsite - Behavioral / Leadership

Apr 2026

Roku data scientist interview with a behavioral round focused on cross-functional collaboration. Pretty standard stuff but worth prepping a solid example ahead of time.

Tell me about a time you worked with cross-functional partners like PMs, engineers, or designers. What was your role, how did you get everyone on the same page, and what came out of it?

“I had an example ready but mid-answer I realized my story made me sound more like a passive observer than someone actually driving alignment.”

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Roku·Data Scientist·Technical Phone Screen

Apr 2026

Roku data science interview with a causal inference question that sounds clean on paper but gets messy fast once you start talking through the assumptions. No fluff, just one meaty scenario.

Roku released an optional smart speaker and wants to know if owning it actually drives more user engagement. Since users self-select into buying it, you can't run a forced experiment. What's your approach to estimating the causal effect, and which design would you go with?

“This is the kind of question where you can tell they want you to go beyond 'compare buyers vs non-buyers' pretty quickly.”

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Roku·Software Engineer·Onsite - System Design / Architecture

May 2026

Roku system design interview focused entirely on building a Netflix-scale video streaming platform. It was a deep technical dive and covered more ground than I expected in a single session.

How would you design the content ingestion and encoding pipeline for a large-scale video streaming service, including multi-bitrate encoding and adaptive streaming?
How would you design the CDN distribution layer to serve video content globally at scale?
How would you structure the video catalog and metadata storage for a streaming platform?
How would you build a recommendations and personalization system for a video streaming service?
How would you implement user playback state, including resume-from-last-position and syncing across multiple devices?
How would you incorporate DRM into the streaming architecture to protect content?
How would you design the system to handle heavily read-skewed traffic, where reads vastly outnumber writes?

“This is where I spent the most time and probably went too deep too fast.”

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Roku·Software Engineer·Onsite - System Design / Architecture

May 2026

System design round at Roku for a software engineer role, focused entirely on ad infrastructure. One meaty question about frequency capping that went pretty deep into distributed systems territory.

Design the frequency capping component of an ad-serving system. How do you prevent the same ad from being shown to the same user too many times within a rolling time window?

“This one sprawled fast.”

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Roku·Data Scientist·Technical Phone Screen

May 2026

Roku data scientist interview that went deep into business analytics for a coffee shop scenario. Three-part case covering profit decomposition, causal inference without an experiment, and rapid experimentation design. Dense and technical, felt more like a consulting case than a typical DS screen.

Build a driver tree and decompose an 18% profit drop across unit volume, pricing and discounting, product mix, COGS changes, waste, and labor productivity. Specify exact formulas and your effect-ordering method.
A competitor opened two blocks away mid-July. Without running an A/B test, how would you estimate the incremental revenue impact on your shop? Walk through your identification strategy, data requirements, assumptions, and at least two robustness checks.
Design two experiments you can run within two weeks to test hypotheses around menu engineering or promotional timing. Include margin guardrails and a stopping rule.

“This is the kind of question where you can sound smart for five minutes and still not actually answer it.”

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Roku·Software Engineer·Hiring Manager Screen

May 2026

Behavioral round for a software engineer role at Roku, driven entirely by leadership principles. Came in expecting maybe two or three questions but they had a story for every principle on the list, plus follow-ups that went deeper than I anticipated.

Tell me about a time you put the customer's needs ahead of what was technically convenient or easy for your team.
Describe a situation where you took ownership of something that was technically outside your responsibility.
Walk me through a time you simplified a complex process or system. What was the before and after?
Tell me about a decision you made with incomplete information. How did you know you were right?
Give me an example of a project where you delivered results under significant constraints.
Tell me about a time you acted quickly without waiting for full alignment. What happened?
Describe a time you dug deep into a problem and found a root cause that wasn't obvious at first.
Tell me about a time you disagreed with a decision but ultimately committed to it. How did you handle the disagreement?

“I had a decent story here but fumbled the follow-up when they asked what data I used to validate that customers actually cared.”

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Roku·Data Scientist·Onsite - Behavioral / Leadership

May 2026

Behavioral round at Roku for a data scientist role, pretty heavy on cross-functional storytelling and communication. One meaty question that required a lot of moving parts to answer well.

Walk me through a time you worked with a PM and an engineer to deliver a data product or analysis that actually changed a business decision. Cover the situation, what you were responsible for, how you influenced people without direct authority, any methodological disagreements you had to work through, and how you aligned on timelines. Include a conflict you de-escalated, a trade-off you made, and what you'd do differently. Then explain how you'd present the same findings differently to a skeptical exec versus a junior engineer.

“This question is a lot.”

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