Interview questions
Data Scientist interview questions
53 realistic questions across technical, behavioural, HR, situational and role-specific categories. Questions only — join free to unlock model answers, quizzes and AI mock interviews.
Showing 25 of 53 questions
Given a data pipeline that processes user events, how would you decide whether to use inheritance or composition for the event handlers?
Technical
Beginner
Q1
How would you design a REST API endpoint for a real-time recommendation system that handles 10,000 requests per second?
Technical
Intermediate
Q2
How would you diagnose and fix a slow SQL query that joins three tables and takes 30 seconds to run?
Technical
Intermediate
Q3
How would you keep a data dashboard page fast when traffic spikes from 100 to 10,000 concurrent users?
Technical
Advanced
Q4
How would you secure a REST API that exposes sensitive user data for a machine learning model?
Technical
Advanced
Q5
Given a data science project with a data pipeline, model training, and a web API, how would you decide what to unit test versus integration test?
Technical
Intermediate
Q6
How would you prevent a race condition when two users update the same record in a distributed system?
Technical
Advanced
Q7
Walk me through deploying a machine learning model to production with zero downtime.
Technical
Advanced
Q8
How would you explain the concept of conditional probability to a colleague struggling with a project involving uncertain outcomes?
Technical
Beginner
Q41
Can you describe a specific project where you identified and corrected data quality issues that significantly changed your analysis results?
Technical
Beginner
Q42
How would you conduct exploratory data analysis on a new dataset to uncover key insights and guide further modeling?
Technical
Intermediate
Q43
Can you walk me through how you would select and implement a machine learning algorithm to solve a classification problem?
Technical
Intermediate
Q44
How would you help a colleague evaluate and validate a predictive model to ensure its reliability?
Technical
Intermediate
Q45
Describe a project where your feature engineering and selection choices significantly improved model performance.
Technical
Intermediate
Q46
How would you design and train a basic neural network to solve an image classification task?
Technical
Advanced
Q47
Can you describe how you would build a big data pipeline to process and analyze streaming data?
Technical
Advanced
Q48
How would you perform time series forecasting to predict future sales based on historical data?
Technical
Advanced
Q49
Can you share an example where your experimental design and causal inference methods helped identify the true effect of a change?
Technical
Expert
Q50
Describe a project where using supervised machine learning algorithms led to a measurable improvement in outcomes.
Technical
Intermediate
Q54
How would you identify and validate clusters in an unlabeled dataset using unsupervised learning techniques?
Technical
Intermediate
Q55
Can you explain how you would design and analyze an A/B test to evaluate a new website feature?
Technical
Advanced
Q60
Tell me about a time when your data wrangling and cleaning efforts uncovered critical insights that changed your project’s direction.
Technical
Beginner
Q110
How would you implement an advanced deep learning model to improve predictive accuracy on a complex dataset?
Technical
Advanced
Q116
How would you design and implement a scalable data processing pipeline using big data technologies to handle terabytes of streaming data?
Technical
Advanced
Q117
How would you use statistical tests to determine if a new marketing campaign has significantly increased sales?
Technical
Beginner
Q167
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