Intuit

Large Enterprises

Most of these Intuit write-ups come from Software Engineers (37), then Data Scientists (17) and Machine Learning Engineers (6). The most reported rounds are the technical phone screen (47), the system design round (7), the product sense round (5) and the online assessment (2).

65 interview notes · updated Aug 2026

Intuit·Software Engineer·Technical Phone Screen

Jul 2026

Intuit coding interview, 90 minutes, four questions covering a mix of graph problems, DP, and array fundamentals. Nothing too wild but the alien dictionary alone could eat up your whole session if you're not careful.

Implement a solution to determine the character ordering in an alien dictionary given a sorted list of words.
Solve the dungeon game problem where you must find the minimum initial health needed to reach the bottom-right of a grid.
Solve an easy prefix sum problem.
Find the median of an array.

“This one took most of my mental energy.”

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Intuit·Data Scientist·Technical Phone Screen

Jul 2026

A fairly intense technical screen for a DS role at Intuit, centered entirely on one long delivery cost case study. The question had a lot of moving parts and I'm not sure I covered everything they were looking for.

A restaurant sees a significant spike in delivery cost per order over the past month. Given tables for orders, courier payments, platform fees, weather, and store operations, how would you first confirm the metric increase is real and not an artifact of how the metric is defined or calculated?
Walk through how you would decompose the increase in delivery cost per order into its component drivers, covering mix effects like platform, distance, zone, and time of day, as well as rate effects like pay per km or surge multipliers, and execution issues like cancellations or SLA breaches.
What causal hypotheses would you consider for why delivery costs increased, and how would you quantify each one? For example, could weather shocks, staffing changes that increase courier wait times at pickup, or platform policy changes be responsible?
Propose two concrete experiments you would run to reduce delivery cost per order. What would your success metrics and guardrails be, and how would you think about statistical power and potential sources of bias?
What are the most common pitfalls when analyzing delivery cost per order in this setup, and how would you guard against each one?

“This part tripped me up more than I expected.”

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Intuit·Software Engineer·Technical Phone Screen

Jul 2026

Intuit software engineer interview with a parsing problem that looks simple but has a real edge case lurking in it. The kind of question where you feel good for about two minutes and then realize you missed something.

Given the output of `ls -l` passed through stdin, write a program that prints the file name of the entry with the largest file size. File names may contain spaces, and you should skip non-entry lines like `total N`.

“I went straight for splitting on whitespace and grabbing index 4 for the size, which works fine until you remember file names can have spaces.”

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Intuit·Software Engineer·Technical Phone Screen

Jul 2026

Interviewed for a software engineer role at Intuit and got a pretty standard digit manipulation problem. Nothing too wild but the carry propagation edge case is where people tend to slip up.

Given an array of digits representing a large integer (most significant digit first), add one to the integer and return the result as a digit array. Handle carry propagation and the case where the number grows an extra digit.

“The basic case is easy enough, just increment the last digit.”

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Intuit·Software Engineer·Onsite - Behavioral / Leadership

Jul 2026

Went through a behavioral round at Intuit for a software engineer role. Pretty standard stuff but the project impact question tripped me up more than I expected.

Walk me through your resume, focusing on your roles, what you were responsible for, and any measurable results you can point to.
Pick a recent project and walk me through your specific contribution, the decisions you made, what you had to trade off, and what the outcome was.
Give me one example each of taking ownership, collaborating with a team, and navigating a situation where things were unclear. What did you take away from each?

“I rambled.”

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Intuit·Data Scientist·Technical Phone Screen

Jul 2026

SQL-heavy technical screen for a Data Scientist role at Intuit. The problem was a single multi-part question built around a subscription analytics table, escalating from basic cohort aggregation to YoY growth rates to a paid-only filter variant. Felt more like a take-home in spirit but was done live.

Given a user-level table with signup and subscription dates, write a query that returns, for each calendar month of signups, the total signups, the count who ever subscribed, and the conversion rate.
Extend the query to compute year-over-year subscription rate growth for each month, defined as the percentage change in conversion rate versus the same calendar month in the prior year. Return NULL if the prior year's month isn't in the data.
Now assume the table includes both free and paid subscription types. Recompute the YoY growth metric but treat only paid subscribers as 'converted'. How does your query change?

“The cohort grouping part was fine, DATE_TRUNC on signup_date and a conditional count on subscription_date not being null.”

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Intuit·Software Engineer·Technical Phone Screen

Jul 2026

Product Analyst case interview at Intuit, centered on a funnel scorecard for a QuickBooks-style product with 15+ access points and very uneven traffic distribution. One meaty analytical scenario, no fluff.

You're looking at a funnel scorecard (Visit to Application Start to Application Complete to Paid) broken out by 15+ access points with heavily skewed traffic. What three insights would you surface, and how do you prioritize them by impact rather than just by rate?
How would you handle the long tail of low-traffic access points in your analysis? There are 15+ entry points and most have very little traffic.
Based on your insights from the scorecard, what product, experimentation, or data work would you recommend as next steps?

“This is where I tripped up a bit.”

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Intuit·Data Scientist·Technical Phone Screen

Jul 2026

Intuit data scientist interview that went deep on A/B testing statistics, like really deep. They wanted full derivations, not just 'run a z-test and move on,' so if you're fuzzy on where the z-test formula actually comes from, this round will find that out fast.

For an A/B test on a binary delivery outcome, which significance test would you use and why is it preferable to a t-test on proportions? Derive the test statistic from first principles starting from the Bernoulli distribution through to the normal approximation, and state the conditions under which that approximation holds.
Using the large-sample A/B test data (control: 920/1000 delivered, variant: 880/1000 delivered), compute the p-value to three significant figures and a 95% confidence interval for the difference in proportions. Show your work.
A small-market rollout gives you much smaller sample sizes: 20 out of 25 delivered in control, 12 out of 18 in variant. How does your test choice change? Walk through whether you'd use chi-square, Fisher's exact, or a z-test, and either compute the exact p-value or explain precisely how you'd get it.
When does a two-sample t-test produce essentially the same result as a z-test for proportions, and when does it break down? Give at least two concrete failure modes.

“This is where I spent most of my mental energy.”

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Intuit·Software Engineer·Technical Phone Screen

Jul 2026

Interviewed at Intuit for a software engineering role and got a string parsing problem that looked straightforward but had a few gotchas buried in the details.

Given a multiline string representing the output of 'ls -l', parse each line to extract the file size and the filename, then return the filename with the largest file size. Note that filenames can contain spaces.

“The spaces-in-filename part is what gets you.”

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Intuit·Software Engineer·Technical Phone Screen

Jun 2026

Coding round at Intuit for a software engineer role. One algorithmic problem with a follow-up that pushed into territory I wasn't totally prepared for.

You're given an array of digits representing a non-negative integer (most significant digit first, no leading zeros). Add 1 to the number and return the updated digit array.

“The base case tripped me up less than I expected.”

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Intuit interview FAQ

What rounds are in the Intuit interview?

Candidates most often report a technical phone screen (47 write-ups), a system design round (7), a product sense round (5) and an online assessment (2).

What does the Intuit technical phone screen cover?

Across 47 technical phone screen write-ups, the most tagged question topics are Technical Trade-offs (51 questions), Product Analytics & Metrics (39) and Algorithms & Data Structures (27).