Interview Experiences

Real candidates, real loops: every round, what was asked, and how it ended.

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50 stories

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DoorDashData Scientist
Feb 2026

Three A/B Testing Cases That Exposed My Blind Spot

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OnsiteXP0
DoorDashData Scientist
Feb 2026

Three Case Rounds, No A/B Testing Background

I'd seen a lot of phone screen reports for this role and passed it pretty easily, but the onsite was like the reports I'd read about — genuinely hard, and unlike anything I'd seen before. My background is as a DS who has always worked on modeling, with a little bit of product analytics experience mixed in. I don't have hands-on experience running A/B tests, so on the onsite, the experiment design…

Onsite0
DoorDashData Scientist
Feb 2026

Onsite ML System Design for the Home Feed Recommender

Problem background: design a store recommendation system similar to the app's home page. Interview process & core follow-ups: Overall architecture and hard constraints The scenario given right away was home page recommendation. User input is extremely sparse — basically just the User ID and current location. The system has a couple of hard constraints: the stores surfaced must be within delivery…

Onsite0
DoorDashData Scientist
Feb 2026

Three Onsite Case Rounds on A/B Testing and Promotions After an Easy Phone Screen

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OnsiteXP0
DoorDashMachine Learning Engineer InternIntern
Feb 2026

LLM Research Questions, Then Ghosted

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No responseTechnical ScreenXP0
DoorDashSoftware EngineerSenior+
Feb 2026

Four Onsite Rounds, Rough Code Craft

Let me start with the technical screen: a fairly classic multi-source BFS problem — find the nearest source for every cell in a 2D grid. Medium difficulty, leaning toward the basic side. Next is the onsite, four rounds in total. Round 1 was system design. The first 15 minutes were spent talking about a recent project of yours, then it moved into the design question. The task was to design an app…

Onsite0
DoorDashSoftware Engineer
Jan 2026

Full Onsite Loop, Then Grilled About Using AI More

DoorDash's full loop. I felt like their question bank isn't very big — pretty much everything is covered by write-ups here already. Specifically, the phone screen with the interviewer: dasher_pay. Same problem that's already been posted here, so pay attention to handling the input datetime. I used a few states to control the order's status. I forgot the follow-up, but again, the situations posted…

RejectedOnsite0
DoorDashData Scientist
Jan 2026

System Design for the Home Feed Recommendation Engine

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OnsiteXP0
DoorDashData Scientist
Nov 2025

Recycled SQL Questions and a Biker-Project Case Round

HR screen -> Round 1 30-min SQL round: 4 old/frequently-asked questions, with my basic approach: Q1. Percentage of high frequency customers (order>30) each month. Get cus_id, month, order_count. Group by month, cus; count(distinct case when oc> then cus end)/count(distinct cus) Q2. Customers who ordered the most, excluding high-frequency customers, each month (follow-up: the most frequent custome…

Technical Screen0
DoorDashData Scientist
Nov 2025

SQL Round Ran Out of Time, Then a Bike Case Study

This was the first interview of this hiring round for me, and I wasn't prepared — I underestimated how much time management the SQL portion would take, and I didn't finish it before time was cut off. The SQL question was a real, previously-reported one. It asked for: Users who spent more than $100 in a month The same as above but excluding the person with the highest spend each month Month-over-m…

Technical Screen0
DoorDashData Scientist
Oct 2025

Biker Feature Case Study Plus a Four-Question SQL Round

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RejectedTechnical ScreenXP0
DoorDashData Scientist
Oct 2025

New Case and SQL Questions on the Phone Screen

DoorDash Data Scientist phone screen — I got new questions on both the case study and the SQL sections. The case study asked what the impact would be if a delivery is late, and what the possible reasons are. Then, based on the reasons I gave, the interviewer asked what data we would look at, and how to decide which of my stated reasons was the most important one. They also brought up that we've n…

Technical Screen0
DoorDashData Scientist
Oct 2025

SQL Screen With Doubled Difficulty and Tight Time

Part 1 was product, and since I was well prepared it felt fine. Prepare a lot more for high-frequency Biker and Cold Food. Read the attached switchback experiment design, randomization, and analysis parts carefully. SQL was not the usual four questions (someone on the forum summarized them before, but the answers weren't quite right, so correct them yourself). I got new questions, and the difficu…

Technical Screen0
DoorDashData Scientist
Oct 2025

Four Onsite Rounds, No Self-Intros, and a Prickly HM

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OnsiteXP0
DoorDashData Scientist
Oct 2025

Missed the Case Answer Until Five Minutes of Hints Got Me There

I had this interview not long ago. The SQL was the classic Delivery set — the overall question volume was pretty large, but not every question required you to actually write it out. Some of them asked how you'd turn an existing query into an aggregated version, and the interviewer just had me talk through how I'd change the query instead of writing the code, to save time. The case question was: c…

Technical Screen0
DoorDashAnalyst
Oct 2025

Seven Rounds Including a Take-home and Two SM Interviews

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OnsiteXP0
DoorDashData Scientist
Oct 2025

Seven Rounds Including a Take-Home Prediction Task

The interview process was as follows: Round 1: HackerRank assessment — SQL plus some data analysis questions. Round 2: HR screen — talked about why I was interested in DoorDash, my project experience, and why I was looking to switch jobs. Round 3: Hiring manager interview — mostly about my project experience, plus a DoorDash case question. Round 4: Take-home — given a DoorDash dataset to build a…

Onsite0
DoorDashData Scientist
Oct 2025

A Seven-Round Loop with a Take-Home and Three Manager Interviews

The interview process went like this: Round 1: HackerRank assessment — SQL plus some data analysis questions. Round 2: HR screen — talked about why I was interested in DD, my project experience, and why I was looking to switch jobs. Round 3: Hiring manager interview — mainly talked about project experience, plus a DoorDash case Q&A. Round 4: Take-home — given a DoorDash dataset to build a predict…

Onsite0
DoorDashAnalytics Engineer
Oct 2025

Rejected After a Four-Round Virtual Onsite

I couldn't find a single interview review for the analytics engineering role on the forum, so I'm contributing one. Tech round: one LC medium question, not sure if it's an original/repeat question, pretty simple but exhausting — window sum, find the max sum. I'd seen it before in DoorDash's DE interview reviews. Then four SQL questions — he said getting three done was actually fine. I wrote the f…

RejectedOnsite0
DoorDashData Scientist
Sep 2025

Behavioral Round, Then a Case Study and SQL

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Technical ScreenXP0

What are interview experiences?

An interview experience is a candidate's own account of a hiring loop — not a question bank entry. It tells you the shape of the process: how many rounds there were, what each round actually tested, how long the gaps between them ran, and what the recruiter said at the end. That context is the part a question list cannot give you.

How to read them

Weight recent write-ups more heavily — interview loops change, often within a year. Read several for the same company and role rather than one: a single account tells you what one interviewer asked, while five tell you what the bar is. Note the outcome badge too, since a rejection write-up usually explains the gap far more precisely than an offer one.

Share your own

Every published experience earns 50 XP, and each of the first 3 likes it receives in a day earns you 10 XP more. Likes must come from established accounts; like-for-like swaps and likes from your own second account are not paid. Write it while the details are fresh — the round order, the exact prompts, and how much time you were given are what the next reader needs.

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