Uber Interview Questions

Uber Coding & Algorithms Interview Questions

Practice 303 real Uber interview questions for 2026. Covers top categories — Coding & Algorithms, Analytics & Experimentation, Machine Learning, Behavioral & Leadership, Statistics & Math — across Software Engineer, Data Scientist, Machine Learning Engineer, and Technical Program Manager roles. Real questions from actual interviews with detailed solutions, focused guidance, and concrete interview preparation so you can practice the exact problem types Uber asks. Expect a coding-heavy loop for software engineering candidates: timed algorithm problems, online-assessment style OAs, and system-design tasks. For Software Engineer roles the recurring technical themes here are algorithm puzzles (kth-smallest-in-BST, knight/grid and reversal problems, prime-ending path counts), OA-style coding questions, and product-oriented design prompts such as a pickup-area driver queue and global nearby-restaurant search. Data Scientist questions center on membership/discount experiments, cold-start restaurant ratings and their launch evaluation, driver-acceptance modeling, and marketplace-impact analyses. Machine Learning Engineer prompts focus on completion-rate gaps, implementing attention and regression models, feed-ranking and restaurant-recommendation design, and pickup-location optimization. TPM items emphasize delivery-address fixes, competitive product comparisons, and leadership stories. Prepare by timing practice coding, rehearsing marketplace case studies, building short model write-ups, and polishing STAR examples for behavioral rounds.

303 Questions 1 Company07.03.2026
Showing 20 results
Role
Uber logo
Uber
Medium
Data ScientistSenior+

Implement Streaming Clustering for Numbers

You receive a continuous stream of numeric values. Choose an appropriate clustering algorithm and implement it so that each incoming number can be ass...

Machine Learning
11
0
76 people solved
Apr 10, 2026
Uber logo
Uber
Medium
Software Engineer

Design an object-oriented parking lot system

Design an object-oriented model for a parking lot management system. Requirements: - The parking lot has multiple levels; each level has multiple park...

Software Engineering Fundamentals
24
0
173 people solved
Nov 2, 2025
Uber logo
Uber
Medium
Data ScientistNew Grad Locked

Predict driver acceptance

This question evaluates a candidate's competency in designing and operationalizing an end-to-end machine learning solution for predicting driver accep...

Machine Learning
5
0
69 people solved
Mar 22, 2026
Uber logo
Uber
Medium
Software Engineer

Design a Rolling Event Counter

Design an in-memory rolling event counter. The counter should support two operations: - record(timestamp): record one event at the given timestamp, me...

Software Engineering Fundamentals
9
0
67 people solved
Jan 30, 2026
Uber logo
Uber
Medium
Software EngineerSenior+

How do you manage performance and disagreements?

Manager behavioral prompts Answer the following as a people manager (or manager-level tech lead). Use real examples where possible. 1. Scope and owner...

Behavioral & Leadership
7
0
114 people solved
Mar 1, 2026
Uber logo
Uber
Medium
Software Engineer Locked

Design and Implement an LRU Cache

This question evaluates a candidate's ability to design and implement an LRU cache data structure with O(1) time complexity for both reads and writes....

Coding & Algorithms
0
0
9 people solved
Jun 8, 2026
Uber logo
Uber
Hard
Software Engineer

Design Uber Eats-style search function

Design the search function for a large-scale food delivery platform similar to Uber Eats. A user opens the app and types a query into a single search ...

System Design
42
0
500 people solved
Nov 11, 2025
Uber logo
Uber
Hard
Software Engineer Locked

Solve Wonderful Strings and Grid Queries

This question evaluates algorithm design and data-structure competencies through two problems: a parity-constrained minimum-cost string transformation...

Coding & Algorithms
3
0
26 people solved
May 13, 2026
Uber logo
Uber
Medium
Software Engineer Locked

Design a Daily Puzzle Platform

This question evaluates backend system-design skills including API design, data modeling, service decomposition, scaling and consistency trade-offs, s...

System Design
5
0
79 people solved
Apr 19, 2026
Uber logo
Uber
Medium
Machine Learning Engineer

Design a restaurant recommendation system

Question Design a restaurant recommendation system for a food delivery marketplace such as Uber Eats. When a user opens the home page, the system shou...

ML System Design
31
0
305 people solved
Dec 15, 2025
Uber logo
Uber
Medium
Software Engineer Locked

Design a meeting room reservation API

This question evaluates a candidate's object-oriented design and algorithmic competence for building an in-memory meeting room reservation API, focusi...

Software Engineering Fundamentals
23
0
184 people solved
Feb 12, 2026
Uber logo
Uber
Medium
Software Engineer

Implement A Concurrent Download De-Duplication Layer

Design and implement a downloader that accepts many URL download requests concurrently. Requests for different URLs should run independently. If sever...

Software Engineering Fundamentals
1
0
12 people solved
Apr 12, 2026
Uber logo
Uber
Medium
Data ScientistSenior+

Design a Maps Address Search Bar

Design the search experience for a map application's address bar, similar to the search box in Google Maps. The system should handle multiple user int...

Analytics & Experimentation
4
0
56 people solved
Apr 10, 2026
Uber logo
Uber
Hard
Data Scientist

Build and assess CTR prediction

CTR Prediction with Delayed Feedback and Extreme Class Imbalance You are building a model to predict the probability that an ad impression results in ...

Machine Learning
11
0
118 people solved
Oct 13, 2025
Uber logo
Uber
Medium
Software EngineerSenior+

Quadtree for 2D Geospatial Points

Quadtree for 2D Geospatial Points Design and implement a point quadtree that stores geographic locations on a 2D plane and supports efficient axis-ali...

Coding & Algorithms
0
0
6 people solved
Jun 28, 2026
Uber logo
Uber
Easy
Data ScientistIntern

Analyze the Accident-Rate Spike

A monthly line chart shows the accident rate for Uber trips in one city. The accident rate increases sharply from June through November, then drops qu...

Statistics & Math
16
0
129 people solved
Feb 12, 2026
Uber logo
Uber
Hard
Data Scientist

Formulate hypotheses and compute AB test significance

A/B Test Snapshot: Pickup ETA Card Experiment You are analyzing a 7-day A/B test with equal allocation. Each request is an exposure; the primary outco...

Statistics & Math
14
0
114 people solved
Oct 13, 2025
Uber logo
Uber
Medium
Software Engineer Locked

Design follow/follower classes

This question evaluates object-oriented design and data-structure modeling skills for directed graphs, testing competency in representing follow relat...

Software Engineering Fundamentals
38
0
345 people solved
Mar 1, 2026
Uber logo
Uber
Hard
Data Scientist

Measure YouTube Ad Effectiveness

Uber is running marketing ads on YouTube and wants to understand whether the campaign creates incremental business value, not just whether users watch...

Analytics & Experimentation
2
0
26 people solved
Jan 29, 2026
Uber logo
Uber
Medium
Machine Learning Engineer

Answer leadership questions on tradeoffs and collaboration

Behavioral / Leadership Questions Answer using specific examples from your experience. 1. Project deep dive: Walk through a recent project end-to-end ...

Behavioral & Leadership
18
0
125 people solved
Dec 15, 2025

Frequently Asked Questions

How hard are Uber interview questions?
Uber interview questions range from moderate to very challenging depending on role and level. Software Engineer loops emphasize data structures, algorithms and system-design problems that often require multi-step solutions and production tradeoffs, so expect mid-to-hard coding and design tasks. Data Scientist interviews skew toward analytics, experimentation and marketplace judgment with case-style product questions that reward rigorous causal thinking. Machine Learning Engineer rounds mix implementation and ML-system design, and TPM questions focus on program delivery and stakeholder tradeoffs. Preparation quality and interview level (junior vs senior) are the main determinants of perceived difficulty.
What is Uber's interview process and which roles ask these question types?
The typical Uber hiring sequence starts with a recruiter screen, followed by one or two technical phone or take-home assessments for some roles, then an onsite or virtual loop of four to six interviews and a hiring-committee review. Software Engineer rounds concentrate on coding, online assessment problems and system design. Data Scientist interviews emphasize SQL, experiments, product-analytics cases and behavioral ownership. Machine Learning Engineer interviews add ML model implementation and productionization questions. Technical Program Manager interviews focus on cross-functional program examples and behavioral leadership. Timelines usually span three to six weeks.
How long should I prepare for an Uber interview and how should I structure my timeline?
Plan your preparation based on role and current skill level. For Software Engineer positions allocate six to twelve weeks focusing on timed coding practice, mock interviews and system-design case work. Data Scientist candidates should budget three to six weeks prioritizing SQL, experimentation, product-case practice and clear storytelling about impact. Machine Learning Engineers need four to eight weeks combining model implementation, systems design and coding. TPM candidates can prepare in two to four weeks concentrating on program examples and stakeholder communication. Include final-week full mock loops and a review of role-specific Uber product scenarios.
Which specific subtopics should I focus on for each position at Uber?
For Software Engineers concentrate on algorithmic patterns seen in past Uber questions: BST kth-smallest, graph and knight problems, two online-assessment algorithm tasks, queue design for pickup-area driver matching, and product-oriented designs like global nearby-restaurant search and trade-off-driven design changes. Data Scientists should drill A/B testing, causal inference, cold-start rating models, marketplace evaluation (driver acceptance, membership and priority delivery impact) and translating analyses into action. Machine Learning Engineers should practice implementing attention, linear and logistic regression, feed ranking and ML-system tradeoffs including pickup-location optimization. TPMs should rehearse unclear-address resolution and cross-product comparisons with crisp ownership stories.
What standout tips and common pitfalls should I know before interviewing at Uber?
Standout tips: always clarify requirements and constraints up front, structure answers around measurable metrics and business impact, and narrate tradeoffs between latency, cost and accuracy. Use concrete examples from marketplace contexts and quantify outcomes when possible. For coding, write clean, testable code and discuss complexity and edge cases. Common pitfalls include skipping assumptions, failing to justify metric choices in product/analytics problems, neglecting production implications for ML designs, and overfitting to toy solutions instead of addressing scale and reliability. End with clear next steps or monitoring plans to show ownership.

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