Data Scientist Interview Experiences & Questions
40 real Data Scientist interviews from 29 companies: what each round covers, the exact questions, and who got the offer.
What to expect · Data Scientist
Based on 40 real interviews
Data Scientist interviews by company
The Data Scientist interview process
Most common round types: Behavioral (11), Statistics & Experimentation (7), SQL (7), Data Analysis (6), Coding (5), Analytical (4).
Real Data Scientist interview questions
- Do you have experience with A/B testing?
- What if we used AI to profile people coming into our brick and mortar bank locations? Would that be ethical?
- Do you want to evaluate a linear regression or a classification and regression tree, and can you walk me through what is wrong with this airline delay model?
- Complete four notebook-style tasks cleaning messy data, summarizing it, and building a basic model in 90 minutes.
- Let's build a schema for this product.
- Write a short shell script to download a package, unzip it, and install it into an Anaconda environment.
- We launched a feature and some metrics went red while others went green. How would you think about the user experience, and would you recommend launching it?
- Given behavioral data from a feature launch or A/B test, how would you define success metrics and decide whether the launch was successful?
- Walk me through the presentation you submitted for the data challenge.
- How does this amusement park make money?
- It was a 30 minute call with 2 SQL questions and one product case study using the tables from the SQL
- Can you walk me through your background and data science experience?
- How do we sample from an arbitrary distribution?
- How do you define success metrics?
- Write SQL to answer progressively harder questions from the tables provided.
- Walk me through this Python script and class, explain what each function is doing, tell me what __init__ is, and say whether these pytest unit tests are sufficient.
- How do you explain p-value?
- How would you improve Dasher ETA?
- Here is some modular AI-generated SQL or Python. What is the logic, and what is wrong with it?
- Basic background conversation. No technical questions.
- Tell me about one specific project you worked on recently.
- How do you calculate a t statistic or a z statistic?
- Find the monthly ratio of high frequency ordering customers(>30) to total no. of customers
- We have cold food that's arriving at the customer and they're unhappy. What would you do to solve it?
- Review this poorly written script and point out the problems.
- We want to redesign a product interface and add new features. How would you go about it?
- Mostly feature engineering, with some core Python (functions and classes) mixed in. The platform has a built-in AI assistant you can query for syntax, so you don't need to memorize every method.
- How do you measure if our current advertising product is working properly or not?
- Walk me through how you'd design the experiment and causal analysis for this problem.
- How will you design an experiment for Uber eats home screen for carousal placement.
- SQL with basic COUNT(*), CTE expressions, no window functions
- how do you calculate power?
- How would you measure success for adding in-store search to grocery on DoorDash?
- Google Meet used to be available only to G Suite users and now it's widely available to everybody. How would you define success and what metrics would you use?
- Find Top 3 drivers in Uber per city per month. Python Pandas based.
- Find seasonality in this quarterly data set.
- what are the estimators you use for DiD?
- How do you justify investing more resources into the new verticals product space?
- How did you make your workplace a better place?
- Find minimum without using minimum function in python
Showing 40 of 133 questions. Open any experience for every question and how the candidate answered.
Latest Data Scientist interview experiences
“Mostly feature engineering, with some core Python (functions and classes) mixed in. The platform has a built-in AI assistant you can query for syntax, so you don't need to memorize every method. You…”
“The interview questions were quite unclear and I had to figure out what she is asking for. Also, she was asking really deep mechanical questions about the estimator I am using and my selection about…”
“The technical round is the hardest to crack.”
“It was nice quite technical and related to adtech. They asked abt ci/cd hub. Model deployment and slopes”
“It was Initial Technical Round to verify the Experience and projects mentioned on the Resume. It also had certain basic fundamental questions”
“You can’t just be like, ‘Oh, I know math.’ You have to translate a business problem into algebra, keep track of the numbers, and still have the business intuition to know what the answer means.”
“good, the process had been very through with a coding round as well.The coding was more on implemneting and solving ML problem”
“Casual and easy. Questions are standard and not difficult. there are many follow up questions though.”
“Overall process was good. The team was very responsive. I think getting behavioral stories really tight might be most important”
“Not that hard, pretty easy SQL coding challenge. Have to run the SQL live in a Python NB. The behavioral was also pretty easy and mostly about past projects and failures and probing more on resume.”
“Interview process went well. It was an internal job posting. Recruiter screen went well and then I spoke with the hiring manager. He then wanted to talk to my current manager at the time to ensure I…”
“Interview was okay. Prepare behavior questions, and SQL questions. SQL involved date calculation, and aggregation”
“First was a recruiter screen, which went in a lot more deeper into experience than normal. Be prepared to share why shopify, deep dive in project Second was tech screen, which was sql & python.…”
“After the recruiter call, the recruiter shared my profile to hiring managers who had headcounts. I talked to one hiring manager, I was asked about my recent projects and some behavioral questions.…”
“The process was fast, recruiter communicated via emails. A technical round with some easy to medium SQL questions and a case study. The final round has 3 case studies and 1 behavioral question round.”
“The process was smooth. The coding assessment(SQL) section needs serious preparation before any attempt. The case study section was as per expecations and followed the generic pattern.”
“Hiring manager asked about AB testing and measurement and campaign through different channel, how to attribute.”
“I was first contacted by the recruiter for a buisness DS position and had a quick screen. They walked me through the several rounds and what is covered in each. Later on they even helped me go…”
“Overall it was a mixed bag, somewhere I felt that I really did well but somewhere I couldn't judge if interviewer is liking my responses. It was very open ended”
“The process was rigorous. Be prepared to explain your projects in depth during the screenings and behaviorals. Be able to answer why you made X decision over Y. For the on-site, it will be in-person…”
“I just found like nervousness dropped my IQ like 20 points, so I ended up doing a lot of mocks with GPT. Then I started seeing way more causal inference in interviews, like the field can go back to…”
“One thing that stood out was the SQL round. They gave me this AI-generated, very modular code and asked me to read the logic like a human, then basically debug what the machine was doing wrong.”
“The round was with the hiring manager, she asked me alot of questions on churn, profit and lifetime value, which was the focus of the team. Others were basic ML questions like bias variance…”
“The process was pretty straightforward. The recruiter reached out over LinkedIn, asked a bunch of questions, and then we went into the case study and the SQL round. I believe I passed the SQL round…”
“The process was good. However, the projects were asked in great detail and one data structure question was asked.”
“It was nothing different than the guide they give you. Just learn everything on there are it is a straight forward interview. It is a rolling hiring so you can schedule your interview a month out so…”
“Overall the interview process was quite quick but also didn't feel very robust as I was expecting for this type of company! I think I failed one of the later technical rounds in the onsite.”
“It was as expected. SQL: First define the metrics and then code them Product sense: How do you measure the success of a product/feature type questions with follow-ups Probability and statistics with…”
“Easier interview, focused on Stats, A/B testing and product sense. First round was technical interview focused on probability and SQL. Final round was on A/B testing, stats, and behavioral questions.”
“It was a good experience but I was able to find something else so I'm glad it didn't work out. The recruiter was nice but the hiring manager seemed a bit distracted and in the end it wasn't a good…”
Frequently asked questions
How many rounds are in the Data Scientist interview?
Candidates report a typical 3 rounds, usually including a recruiter screen, online assessment, phone screen, take-home assignment.
How hard is the Data Scientist interview?
Candidates rate it 3.0/5 on average (medium), across 40 interviews.
How long does the Data Scientist hiring process take?
About 3 weeks from first contact to decision, based on reported timelines.
What percentage of Data Scientist candidates get an offer?
38% of candidates with a final result got an offer (13 of 34).
What does the Data Scientist interview focus on?
The most common round types are Behavioral, Statistics & Experimentation, SQL, Data Analysis.