Instacart Interview Questions — Page 12

Instacart·Data Scientist·Technical Phone Screen

Jul 2026

A product analytics case from Instacart focused on diagnosing a drop in D14 retention. The whole thing was about separating a real signal from a measurement artifact, which is trickier than it sounds when cohort maturity is involved.

A dashboard shows a sharp decline in D14 retention over the past week. Walk through how you'd figure out if this is a real product problem or just a measurement artifact.

“The maturity angle is what trips people up here and I almost glossed over it too.”

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Instacart·Software Engineer·Technical Phone Screen

Jul 2026

Debugging round at Instacart for a software engineering role. One question, one bug, pretty contained scope but the detail that tripped people up was subtle enough that I can see why it makes a good filter.

You're given a function that should return an athlete's personal best score across completed attempts of an event. A test expects 17 but the function returns 13. Find the bug and fix it.

“The fix itself is one line basically, but I spent way too long staring at the score comparison logic before I even thought to check whether the function was filtering on attempt status.”

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Instacart·Software Engineer·Technical Phone Screen

Jul 2026

Got a coding question at Instacart that looked simple on the surface but had enough edge cases to make you second-guess yourself the whole way through.

Given a log of worker entry and exit events, implement a method that returns all intervals during which the worker was present in the office.

“Spent the first few minutes just thinking about what the input actually looked like.”

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Instacart·Data Scientist·Technical Phone Screen

Jul 2026

Senior DS loop at Instacart focused entirely on marketplace analytics and experimentation. Four meaty questions across metric debugging, experiment design, result interpretation, and retention cohort analysis. No fluff, no behavioral stuff, just back-to-back case questions the whole time.

A key marketplace metric has dropped over the past two weeks. Walk through how you'd figure out if the decline is real and what's causing it, covering data quality, seasonality, supply-demand dynamics, user segments, and external factors.
Design an experiment to test a new shopper pricing model that pays more during peak hours. Cover the randomization unit, how you'd build comparable market pairs, pre-period balance checks, success and guardrail metrics, and how you'd handle spillover and seasonal noise in the analysis.
The experiment is done. Profit per order (the pre-declared north star) went down, but average order volume went up. Do you recommend launching? How do you think through a negative primary metric against positive secondary ones, and when is a no-launch still the right call?
A dashboard shows D14 retention dropped sharply for the most recent cohort, while older cohorts look fine. How do you figure out if this is a real problem versus an artifact of immature cohorts, ingestion lag, or a metric definition issue?

“This one felt open-ended enough that I spent probably too long on the data quality angle before getting to the interesting stuff.”

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Instacart·Data Scientist·Technical Phone Screen

Jul 2026

Technical phone screen for a Data Scientist role at Instacart. One meaty coding problem the whole time, no small talk, just straight into the implementation.

Implement a pivot table operation from scratch: given a list of row dicts and a pivot spec (index columns, column columns, values column, and an aggregation function), return the pivoted result as a nested dict or 2D structure.

“This felt more like a data engineering question than a data science one, which threw me a bit.”

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Instacart·Software Engineer·Technical Phone Screen

Jul 2026

Instacart software engineer round that was basically one big coding and design question wrapped together. The problem sounded like a data wrangling exercise but they kept pushing on edge cases and scalability until it felt like a system design conversation.

Given a list of records each containing a date string, store ID, a metric name, and a value, write code to pivot the data so each (store, date) pair becomes one row with columns for sales, refunds, and visits. Missing metrics should default to 0, rows should be sorted by date ascending per store, and you cannot use any date or time libraries.
How would you handle malformed date strings, duplicate entries for the same store, date, and metric combination, and inputs too large to fit in memory?

“The no-date-library constraint is where I almost tripped myself up.”

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Instacart·Software Engineer·Technical Phone Screen

Jul 2026

SQL interview at Instacart for a software engineer role. Two related food delivery problems back to back, the second being a harder extension of the first.

Write an SQL query to find the percentage of orders where the customer's preferred delivery date matches the order date (same-day orders), rounded to two decimal places.
Extend the previous query: for each customer, identify their very first order, then compute the percentage of customers whose first order was a same-day delivery.

“Pretty standard aggregation query.”

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Instacart·Software Engineer·Technical Phone Screen

Jul 2026

Instacart coding screen focused on extending a task manager system, which sounds simple but required thinking carefully about state management and sorted output. Pretty standard technical phone screen format.

Given an existing task manager, add an updateTaskPriority(task_id, delta) method and a getSortedPrioritizedTasks() method that returns tasks ordered by priority, where each task starts at priority 0.

“The delta part tripped me up more than I expected.”

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Instacart·Software Engineer·Onsite - System Design / Architecture

Jul 2026

Instacart software engineer interview with a deep-dive project question that basically asks you to narrate your entire engineering career in one answer. Heavy on architecture, trade-offs, and postmortem thinking.

Walk me through the most complex end-to-end project you led or meaningfully contributed to, covering the problem scope, architecture decisions, trade-offs you made, how you worked with other teams, how you handled risk, how you measured success, and what you'd do differently.

“This question is a beast.”

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Instacart·Data Scientist·Hiring Manager Screen

Jul 2026

Interviewed for a Data Scientist role at Instacart and got hit with some pretty introspective questions about what I actually want from a job, not just what I can do. Felt more like a values alignment conversation than a technical screen.

What are the top five things you need from your next role, how do you rank them, and what are the minimum thresholds you'd accept for each?
Walk me through how you'd evaluate in the first 90 days whether this role is actually a good fit for you, including what signals you'd look for and what would make you decide it isn't working.
What is one absolute dealbreaker for you in a role, and what is one dimension where you're genuinely flexible?

“This tripped me up more than I expected.”

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