
Shopify Data Scientist Interview Questions
& Process
Real candidates share what happened, how many rounds they had,
and how the experience turned out.
Based on 94 interview experiences · FREE TO READ
Candidate interview experiences
First-hand accounts from people who interviewed at Shopify.
Data Scientist
It was a thorough process with several rounds: 1 general aptitude test, 1 pair-coding session, 1 'life story' interview, and then 3 rounds of final technical interviews. These technical interviews focused on past projects and product sense, and the last one was a team-matching session. The interviews felt relevant to the job with practical questions, and the interviewers were very friendly. They emphasized my approach to problem-solving and communication more than reaching a perfect solution. My recruiter was very responsive and communicative throughout the process, with fast turnarounds.
- Can you walk me through a project where you played a significant role?
Senior Data Scientist
This was the longest interview process I've ever been through. It involved an interview with the hiring manager, a SQL pair programming session, data interpretation, a case study, a reverse case study, and a final interview. It wasn't particularly challenging, just that there were too many steps involved. It seemed like they were still figuring out their process because some interviewers didn't know what I was interviewing for or where I was in the process. Since the posting is evergreen, it's hard to know the exact job you're interviewing for, which made navigating the process more difficult.
- Can you explain this visualization?
Staff Data Scientist
The interview process had 4 stages. First was a behavioural and life story interview. Second was a pair programming session that included SQL and Python. For SQL, it involved simple queries and advanced window functions. For Python, I had to fix a bug in a class with 3 methods and add more features, also updating unit tests. I stopped after this stage, even though I did well in the pair programming. The 3rd and 4th stages would have been a technical deep dive and then a leadership review. I didn't like being ghosted after the interview, especially since the interviewer gave positive feedback and discussed next steps.
- There were 4 stages: 1. Behavioural and Life story, 2. Pair Programming (combined SQL and Python) - SQL was more of simple queries with some use of advanced window functions. Python was where there were 3 methods in a class and you had to fix a bug and develop more features. There were some unit tests that you had to update along the way. This is where I stopped even though I did well on the pair programming. 3rd and 4th stage would have been technical deep dive and then leadership review. What I dint like was being ghosted even though the interviewer had all positive comments at the end of the interview and was talking about the next steps.
Shopify Data Scientist Interview Questions
Quoted word for word from Shopify interview reports.
“Given a dictionary mapping groups to proportions (e.g., {‘a’:.25,’b’:.25…}), create a function that takes a number of random inputs and returns the group assignments based on those proportions.”
Read reports →“Could you write a basic string manipulation function in Python 2?”
Read reports →“Given a bit string with question marks, like 11?100, can you write a method to replace the question marks with 1s and 0s? The expected output for the example is 110100 and 111100. This method should be able to handle multiple question marks.”
Read reports →“Can you write a program to generate all possible permutations for given binary strings (strings of 0s and 1s)?”
Read reports →“What is a median and how would you calculate it for a dataset that's too big to fit in memory?”
Read report →“Can you write a SQL query to find the count of active shops at the start of every month?”
Read report →“Can you debug this Python code involving nested dictionaries and execute the provided tests?”
Read report →“How would you filter a list of (date, duration) tuples by a specific time period and compute summary statistics like the average and rolling sum?”
Read report →“Can you fix the bugs in this Python code and also add new features to it?”
Read report →Formats, difficulty and experience
Across all 94 Shopify interview reports.