Data Scientist Machine Learning Interview Questions
Practice the exact questions companies are asking right now.
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Design robber detection from surveillance video
You’re a Data Scientist on a team building a computer-vision system for public-safety monitoring. Problem Design an ML system that uses fixed surveill...
Predict Bike Dock Demand
You are working on a docked bike-sharing system. Build a model that predicts how many bikes will be checked out from a specific dock in the next hour....
Design a Homepage Store Recommender
You are designing the homepage store recommendation system for a food-delivery app similar to DoorDash. When a user opens the app, the online request ...
Debug and fix a PyTorch Transformer training loop
Minimal Causal LM Debugging and Optimization Context You are given a tiny causal decoder-only language model implemented in PyTorch. It appears to "tr...
How predict vehicles’ turn direction at intersection?
At an intersection, there are N vehicles stopped or moving slowly. For each vehicle you have historical time-series data up to the current time: - Pos...
Compare two rare-event detection models statistically
You are evaluating two models (Model A and Model B) for rare-event detection (e.g., fraud, abuse, medical adverse event). Positives are extremely rare...
Design a short-video recommender system
ML System Design — Short-video recommendation Design an end-to-end recommendation system for a short-video feed (TikTok/Reels-style). Walk through the...
Explain KNN and how to tune it
K-Nearest Neighbors (KNN) fundamentals You are interviewing for a Data Scientist role. 1. Explain how the KNN algorithm works for both classification ...
Predict bike demand and avoid overfitting
You are given historical data for a city bike-sharing system. Available fields include station_id, hourly timestamp, number of bike pickups and return...
Design multimodal deployment under compute limits
You need to answer a set of questions related to multimodal model deployment and post-training optimization in an interview. Provide systematic explan...
Design a lead-scoring model
Context You are interviewing for a Data Scientist role on a marketing/growth team. The business wants lead scoring: ranking or scoring incoming leads ...
Handle imbalance, validate samples, and avoid overfitting
Answer the following applied ML questions. 1) Class imbalance You’re building a binary classifier where positives are rare. - What are practical ways ...
Implement K-means and handle train-inference mismatch
Part A — K-means (implementation + concepts) You are given a dataset \(X \in \mathbb{R}^{n \times d}\) and an integer \(k\). 1. Explain K-means: what ...
Design homepage store recommendations
Design a DoorDash-like homepage recommendation system for local stores/restaurants. Request context - The online request contains very little informat...
Compute and plot a precision–recall curve
Precision–Recall (PR) curve coding / evaluation You are given a binary classifier’s outputs on a dataset: - y_true: array of true labels in \(\{0,1\}\...
Design features for house price prediction
Scenario You are building a model to predict house sale price from a tabular dataset (similar to typical real-estate datasets). The interviewer expect...
Explain project details, PCA, and SHAP
Interview prompt (ML project deep dive) You are interviewing for a Data Scientist role. The interviewer asks you to pick one ML project you have perso...
Handle imbalance, sampling, and overfitting
Practical ML questions (classification and generalization) Answer the following ML engineering/data science questions. A) Class imbalance You’re train...
How would you design an ETA prediction system?
Design an end-to-end ETA (Estimated Time of Arrival) system for a maps / ride-hailing / delivery product. Assume users request an ETA for a trip from ...
Explain core probability and ML statistics concepts
Answer the following short theory questions (you may use equations and brief examples): Probability 1. You roll two fair six-sided dice. - What is ...