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Gusto interview notes, page 1 of 2

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Screna has 12 Gusto interview write-ups. The most reported round is the technical phone screen (6).

12 interview notes · updated Jul 2026

Gusto·Product Manager·Onsite - Product Sense / Strategy

Apr 2026
Gusto PM interview with a market sizing question about Google's Project Loon. Pretty niche topic for a payroll company but here we are.
  • Estimate the total market value of Google's Project Loon, the initiative that used IoT devices to bring internet connectivity to rural and remote regions.

“Wasn't expecting a market sizing question about a defunct Google moonshot at a company that does payroll software.”

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Gusto·Software Engineer·Technical Phone Screen

May 2026
Interviewed for a SWE role at Gusto, got a practical coding question about building a feature for displaying a weekly lunch menu. Pretty straightforward but there's more to it than the prompt lets on.
  • How would you design and code an app that displays a weekly lunch menu?

“Seemed simple at first and I kind of underestimated it.”

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Gusto·Product Manager·Onsite - Product Sense / Strategy

May 2026
Gusto product design interview, one question about building a 2FA feature. Short prompt but there's a lot hiding underneath it if you're not careful.
  • Design a two-factor authentication product for Gusto.

“I jumped straight into SMS vs authenticator apps and kind of forgot to anchor on who the users actually are.”

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Gusto·Data Scientist·Hiring Manager Screen

May 2026
Two-part process for a Data Analyst role at Gusto: a hiring manager phone screen followed by a broader behavioral round open to the whole company. Pretty standard stuff but the customer-focus angle came up constantly, so if you're not ready to tie everything back to that you'll feel it.
  • Walk me through your analytical background and explain how it sets you up for this role.
  • Tell me about a time you worked with a non-analytics team and had to make complex data findings understandable and useful for them.
  • Describe a project that went sideways. What happened and what did you take from it?

“I rambled a bit here.”

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Gusto·Data Scientist·Technical Phone Screen

May 2026
Gusto data science interview with a pretty involved A/B testing question that covers everything from p-values to multiple comparisons to a final ship decision. One question but it has a lot of layers, felt more like a take-home problem than a quick phone screen.
  • You ran an A/B/n experiment with one control and two treatment variants. Given a table of aggregated results (group, users, conversions), write Python to compute p-values for each variant vs control, provide 95% confidence intervals for the lift, explain how you'd handle multiple comparisons, and make a ship or no-ship recommendation with reasoning.

“This one took me a while to fully unpack.”

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Gusto·Product Manager·Onsite - Product Sense / Strategy

May 2026
PM interview at Gusto with a product sense question about expanding an existing platform into a new vertical. Pretty straightforward setup but the question had more depth than I expected once I started talking through it.
  • How would you evaluate whether OpenTable should expand its reservation product to cover desks and office spaces?

“I jumped straight into user segments and kind of skipped the 'should they even do this' part, which I think hurt me.”

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Gusto·Software Engineer·Onsite - System Design / Architecture

May 2026
Gusto system design round focused entirely on a shift scheduling platform for a restaurant chain. Pretty deep dive covering data modeling, service architecture, and scalability concerns. Felt like a reasonable scope for the time given, though the Friday publish spike discussion caught me a bit flat-footed.
  • Design a shift scheduling system for a company that operates many restaurants, where managers publish weekly schedules every Friday for their employees to view.
  • How would you structure the backend services for this system, covering schedule creation, publishing, employee access, and notifications?
  • How do you handle the scalability challenges here, particularly the read-heavy access pattern employees create throughout the week and the spike in write traffic every Friday when managers publish schedules?

“I started with the data model because that felt like the safest ground.”

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Gusto·Data Scientist·Online Assessment (OA)

May 2026
SQL screen for a Data Scientist role at Gusto, working with payroll-flavored data. One question, pretty focused, felt like a real-world task more than a leetcode puzzle.
  • Given an employees table and a payroll transactions table, write a SQL query that calculates each employee's total net pay (gross minus deductions) for Q1 2023, then finds the percentage change in net pay between their two most recent pay periods and filters to only employees whose net pay went down.

“Two-part question which tripped me up a bit.”

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Gusto·Data Scientist·Technical Phone Screen

May 2026
Gusto data scientist interview with a meaty A/B testing question that covered the full stack: stats, multiple comparisons, confidence intervals, and a ship decision with stakeholder communication. Pretty involved for a single problem.
  • Given aggregated results from an A/B/n experiment with one control and two treatment variants (each with 50k users and differing conversion counts), compute p-values for each variant versus control using a proportions test in Python.
  • With two variants being tested simultaneously, how do you handle the multiple comparisons problem? Apply a correction method and report your adjusted conclusions.
  • Construct 95% confidence intervals for the absolute and relative uplift of each variant versus control.
  • Make a ship or no-ship recommendation based on the experiment results, and walk through what additional checks you'd run before actually launching. How would you communicate uncertainty to non-technical stakeholders?

“This part I felt okay about.”

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Gusto·Data Scientist·Technical Phone Screen

Jun 2026
A mini case interview at Gusto for a data scientist role, run by a senior analyst. One scenario-based question about diagnosing a payroll metric change. Pretty structured format, felt more like a working session than a traditional interview.
  • Payroll processing time went up 15% month over month. Walk through how you'd use data to figure out why, and what you'd recommend doing about it.

“I jumped straight into hypotheses which felt right but I skipped over clarifying what 'processing time' even meant and that came back to bite me a little when they pushed on whether I meant end-to-end or just a specific step.”

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