J'ai postulé via un établissement d'enseignement supérieur ou universitaire. J'ai passé un entretien chez Toast Inc (Bengaluru) en déc. 2025
Entretien
It was an on campus opportunity. It had one test round for selection which was offline MCQ test. It consisted of 30 easy to medium CS fundamentals questions including DSA, OOPS, DBMS, and Computer Networking
Then it was followed by two technical rounds. In one they ask basic questions about SQL, ML (easy to medium level) then resume in another round.
After that it is followed by cultural round.
J'ai postulé en ligne. J'ai passé un entretien chez Toast Inc (New York, NY) en sept. 2022
Entretien
First step was phone screen, second was a chat with hiring manager, then a take home technical screen, followed by a case study presentation to team members, and lastly a product interview with a senior PM. I only got to the technical screen.
Questions d'entretien [1]
Question 1
Tell me about the ML project you did in the past? Explain how you designed the ML system design?
J'ai postulé en ligne. Le processus a pris 2 semaines. J'ai passé un entretien chez Toast Inc en juil. 2022
Entretien
Tldr: Was rejected and ghosted after passing all test cases in 4 hour HackerRank.
Contacted by recruiter after online application and set up time for a phone screen.
Recruiter missed first scheduled phone screen with no notice. I emailed him 20 minutes after our scheduled meeting time to which he replied he got stuck on something (it was lunch time on a Friday so take that as you will).
Rescheduled for the next week and actually had the call. Standard phone screen stuff. More questions on my own interests/what I was looking for than subject expertise. Was fairly transparent on compensation which was nice but it was a little on the low end. Recruiter was nice enough on the call but was oddly unpleasant over email.
Next step was zoom with the head of data science. Mostly on work experience and previous projects.
Next step was a 4 hour HackerRank assessment. Four shorter questions (string/list manipulation in python, basic SQL, 2 stats Qs) and one longer exercise involving data analysis and model application in a notebook environment. The notebook exercise involves a bit of a trick question with unbalanced data sets.
My answers passed all provided test cases and after submitting my assessment I googled all the questions (they are pretty standard and easily locatable online) and confirmed I did indeed provide optimal solutions for the first 4 questions. The 5th question is of course subjective, as they want to see your process, but I passed their required benchmark metrics in the exercise brief (also without using imported packages which they say "bonus points for" in the brief) and provided extensive comments in my notebook. I even made sure to follow the steps I laid out in an answer for a question about project flow with the data science director which he praised on call.
I received an email a few days later saying I did not do well enough on the assessment and was rejected. I replied asking for further feedback and was ghosted. This would really be fine if the first four questions weren't so easily found online to verify the right answers and if they preferred I used a different thought process on the notebook question then they should say as much when asked for feedback.
I understand a need to verify applicant skill but I believe demanding a 4 hour assessment and then ghosting instead of providing feedback for an experienced hire is just disrespectful of the applicant's time. If your organization does not have the decency to provide feedback or at least to respond to the email asking for it, then you cannot demand four hours of uncompensated work from your applicants.
Questions d'entretien [1]
Question 1
Be ready to describe your projects and to focus on previous collaboration with data engineers and non technical stakeholders.