Interview Experiences

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

Share yours, earn XP

23 stories

Likes earn the author +10 XP for the first 3 likes each day

DoorDashData Scientist
Reported Jul 2026

DoorDash Data Scientist interview: SQL and ambiguous cases

The first round combined a 30-minute SQL assessment and a case study. SQL felt very easy, while the case portion was more difficult: two prompts were straightforward and one was genuinely ambiguous. The next round included three case studies and an interview with a cross-functional partner. The interviewers were kind, but I still had to keep structure and clarity across the scenarios. I did not r…

Technical Screen0
DoorDashData Scientist
Reported Jul 2026

DoorDash Data Scientist interview: SQL and case rounds with one missed concept

After a recruiter screen, I had two screening rounds involving SQL and a case study, followed by more case-study rounds. The onsite-style loop also included a meeting with a cross-functional partner, and I later spoke with a hiring manager. The setup was professional and moved quickly. The data-science questions were not easy. I had done well on the early screens and one case, but a later case br…

HR Screen0
DoorDashData Scientist
Reported Jul 2026

DoorDash Data Scientist interview: take-home after manager screen

I had a quick phone screen and then a Zoom meeting with the hiring manager that lasted about 30 minutes. After that, I completed a take-home assignment and submitted it within 72 hours. That was the end of the process for me. My submission did not move forward, and I did not get another live round. The path looked straightforward on paper, but it was still frustrating because all of my momentum r…

RejectedHR Screen0
DoorDashData Scientist
Reported Jul 2026

DoorDash Data Scientist interview: SQL round and case study before a quick rejection

The loop felt almost entirely about training the interviewers. There was no separate recruiter screening call. It began with a SQL round, then a case study. The recruiter mostly gave a brief introduction, while the two technical sessions carried the process. I finished the SQL questions and explained my thinking to the recruiter as things moved along. The case study also went well, and it felt li…

RejectedTechnical Screen0
DoorDashData Scientist
Reported Jul 2026

DoorDash Data Scientist Interview Experience: SQL, cases, and virtual onsite

An HR-style call covered the role, compensation and benefits, and the hiring flow. The technical screen began with four medium SQL questions in a HackerRank-style format. I barely had time for the last one and got the impression they did not expect a full solution. A case study followed, where I explained how I would approach an open-ended business problem. After passing, I had a virtual onsite w…

0
DoorDashData Scientist
Mar 2026

System Design for the Home-Page Recommendation Feed

Locked — open it to unlock the full story with XP.

OnsiteXP0
DoorDashData Scientist
Mar 2026

Three Onsite Cases All About A/B Testing I Wasn't Ready For

Locked — open it to unlock the full story with XP.

OnsiteXP0
DoorDashData Scientist
Feb 2026

Three A/B Testing Cases That Exposed My Blind Spot

Locked — open it to unlock the full story with XP.

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

Locked — open it to unlock the full story with XP.

OnsiteXP0
DoorDashData Scientist
Jan 2026

System Design for the Home Feed Recommendation Engine

Locked — open it to unlock the full story with XP.

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

Locked — open it to unlock the full story with XP.

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

Locked — open it to unlock the full story with XP.

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
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

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.

Share your experience to earn XP