Uber
Ride-hailing and delivery platform with massive real-time data challenges.
4 Rounds
~21 Days
Hard
The Interview Loop
Recruiter Screen (30 min)
Standard fit check, behavioral questions, and resume overview.
Technical Loop (3-4 Rounds)
Deep dive into domain knowledge, coding, and system design.
Interview Question Bank
Data Scientist
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Behavioral
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medium
Tell me about a time you discovered a significant flaw in your data or model after it was already shared with stakeholders. How did you handle it?
#Communication
#Integrity
#Stakeholder Management
Data Scientist
•
Behavioral
•
easy
Describe a time when you had to explain a complex statistical concept (like p-values or causal inference) to a non-technical product manager.
#Cross-functional Collaboration
#Data Storytelling
Data Scientist
•
Coding
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medium
Write a SQL query to find the 7-day rolling average of driver cancellation rates for each city. Assume you have a trips table with trip_id, city_id, driver_id, status (completed, cancelled_by_driver, cancelled_by_rider), and request_timestamp.
#Window Functions
#Rolling Averages
#Aggregations
Data Scientist
•
Coding
•
medium
Given a list of driver locations (x,y coordinates) and a rider's location, write a Python function to find the k-nearest available drivers. Optimize for performance assuming millions of drivers.
#Heaps
#Spatial Data Structures
#Python
Data Scientist
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Coding
•
medium
Write a SQL query to identify riders who have taken a trip in at least 3 different cities within a 30-day window.
#Self Joins
#Date Functions
#COUNT DISTINCT
Data Scientist
•
Coding
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medium
You are given a dataset of Uber rides. Write a Python script to simulate a simple Markov Chain to predict the probability of a driver ending up in City B given they started in City A.
#Probability
#Markov Chains
#Python
#Data Manipulation
Data Scientist
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System Design
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hard
Design a machine learning system to predict the Estimated Time of Arrival (ETA) for a trip. What features would you use, and how would you evaluate the model?
#ETA Prediction
#Feature Engineering
#Regression
#Model Evaluation
Data Scientist
•
System Design
•
medium
How would you build a model to detect fraudulent rider accounts that are creating fake trips to cash out driver referrals?
#Fraud Detection
#Anomaly Detection
#Classification
Data Scientist
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System Design
•
hard
Design the surge pricing algorithm. What are the key inputs, what is the objective function, and how do you balance rider conversion with driver supply?
#Dynamic Pricing
#Marketplace Equilibrium
#Optimization
Data Scientist
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System Design
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hard
How would you design a matching algorithm for UberX Share (formerly UberPool)? What trade-offs do you need to consider between match rate, detour time, and rider experience?
#Graph Algorithms
#Optimization
#Heuristics
#Marketplace Routing
Data Scientist
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Technical
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hard
Uber wants to test a new driver matching algorithm. However, drivers and riders share the same marketplace, meaning a standard A/B test might suffer from interference. How would you design this experiment?
#A/B Testing
#Switchback Testing
#Network Effects
#Marketplace Interference
Data Scientist
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Technical
•
hard
We rolled out a new driver incentive program in Chicago last month without an A/B test. How would you estimate the causal impact of this program on driver supply?
#Difference-in-Differences
#Synthetic Control
#Observational Data
Data Scientist
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Technical
•
medium
Uber Eats is considering launching a new 'Healthy Options' carousel on the home screen. What metrics would you look at to determine if this feature is successful?
#Product Metrics
#Uber Eats
#Cannibalization
Data Scientist
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Technical
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medium
Suppose the number of completed UberX trips drops by 10% week-over-week, but the number of active app opens remains the same. Walk me through how you would investigate the root cause.
#Root Cause Analysis
#Funnel Analysis
#Marketplace Dynamics
Data Scientist
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Technical
•
hard
We want to introduce a subscription pass (Uber One) that gives free delivery and discounted rides. How would you determine the optimal monthly price for this pass?
#Pricing Strategy
#LTV/CAC
#Elasticity
#Subscription Models
Difficulty Radar
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Meet Your Interviewers
The "Standard" Interviewer
Senior EngineerFocuses on core competencies, system constraints, and clear communication.
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Think Out Loud
Always explain your thought process before writing code or drawing architecture.