Robinhood Data Scientist Interview Questions
& Process
Real candidates share what happened, how many rounds they had,
and how the experience turned out.
Based on 32 interview experiences · FREE TO READ
Candidate interview experiences
First-hand accounts from people who interviewed at Robinhood.
Robinhood
Data Scientist
Senior Average Negative experience No offer 3 rounds
Interview process
Recruiter call Technical screen Onsite
Interview formats
Technical Case Technical
Started with a phone call from a recruiter. If that went well, I had a virtual technical screen. If I passed the technical screen, I had a virtual onsite interview. The product sense and SQL parts were pretty easy. The stats question was a bit tough, though. Unfortunately, it felt like the interviewer wasn't really engaged, maybe they'd already decided. Also, the interviewer's accent was really thick and hard to understand, which made the whole thing a bad experience.
Confirmed questions3 questions
- Tell me about product sense.
- How would you approach this SQL problem?
- Can you answer this statistics question?
Robinhood
Data Scientist
Mid Average Positive experience Accept offer 3 rounds
Interview process
Recruiter call Technical screen Onsite Panel Presentation Offer
Interview formats
Behavioral Technical Coding
Robinhood's interview process feels professional but also welcoming. For me, it was 3 rounds. The first round was a screening interview. It was supposed to be a phone call, but since I live nearby, I got to do it on-site for about 30 minutes. We discussed my background in research and data science. The second round was an on-site interview with four 45-minute sessions: an open-ended data science session, a white-board programming task, an on-computer programming task, and another open-ended data science session. The third round involved meeting with a co-founder to discuss the company's mission. Overall, the interview experience was a great opportunity for me to tackle interesting problems and see the company's passion.
Confirmed questions4 questions
- What makes an investor 'good' in your view, and what methods would you use to find them?
- Could you explain churn and how we might forecast a customer's likelihood to churn?
- Imagine you have an array of numbers indicating the heights of 2-d mountains; calculate the water that would be trapped after it rains.
Robinhood
Data Scientist
Mid Easy Negative experience No offer 1 round
Interview process
Take home Recruiter call
Interview formats
Technical Case
They asked me to book a time to get a 48-hour data science challenge. It covered basic probability and ML, plus a case study to predict churn from given data. I'm pretty sure I nailed the first three questions. For the case study, I found all the required metrics and even did an extra analysis that wasn't asked for. After that, I had to chase the recruiters, and eventually, they told me I 'wasn't a good fit.' Since I thought I did really well, I asked for feedback to understand what went wrong. They said the company has a 'no-feedback' policy, so they couldn't share anything. A total waste of a day, and I don't even know why I was rejected. While they didn't ghost me, it was like getting zero learning experience.
Confirmed questions1 question
- Could you predict user churn based on the provided case study?
Robinhood Data Scientist Interview Questions
Quoted word for word from Robinhood interview reports.
“What's the probability of both event A and event B occurring simultaneously?”
Read reports →“Imagine a square grid with numbers in each spot. If you start at the top-left corner and can only move down or right, what's the maximum number you can achieve when you reach the bottom-left corner?”
Read reports →“Could you explain how to interpret logistic regression coefficients?”
Read reports →“Find Fraud Users probability, random probability etc”
Read reports →“Explain logistic regression.”
Read report →“Regarding mixed marketing spending, specifically on a billboard, how would you determine if that spending was effective, given that multiple other variables are also in play?”
Read report →“How would you write a SQL query to catch a fraud based on transaction data?”
Read report →“What metrics would you use for a classification problem with imbalanced data?”
Read report →“Can you explain the details of ML optimization algorithms like Gradient Descent?”
Read report →Formats, difficulty and experience
Across all 32 Robinhood interview reports.