Uber interview questions

Showing 151–180 of 217 results

• Implement FizzBuzzMedium

  This problem tests foundational programming skills by requiring the implementation of conditional logic and string manipulation based on modular arithmetic patterns.

  UberData ScientistCoding & AlgorithmsOnsite
• Implement Last-Click Attribution APIsMedium

  This problem tests your ability to process streams of events to perform stateful attribution, requiring efficient data structures to track user sessions and match conversions to the most recent preceding click.

  UberSoftware EngineerCoding & AlgorithmsTechnical Screen
• Implement Minesweeper and Word SearchMedium

  This problem tests your ability to manipulate 2D grids using BFS/DFS for board traversal and randomized state generation.

  UberSoftware EngineerCoding & AlgorithmsOnsite
• Implement Multi-Head Self-AttentionMedium

  This question tests the ability to implement the multi-head self-attention mechanism from scratch using PyTorch, focusing on tensor manipulation, linear projections, and the scaled dot-product attention formula.

  UberMachine Learning EngineerMachine LearningTechnical Screen
• Implement Store AutocompleteMedium

  This problem tests proficiency with prefix-based data structures and efficient string retrieval, specifically requiring a design that optimizes for frequent search operations over a static list of store names.

  UberSoftware EngineerCoding & AlgorithmsTechnical Screen
• Implement Streaming Clustering for NumbersMedium

  This question evaluates a data scientist's competency in online clustering for numeric streams, testing understanding of streaming algorithms, bounded-memory cluster summaries, online updates, and issues including initialization, convergence behavior, outlier handling, and concept drift.

  UberData ScientistMachine LearningOnsite
• Implement a Referral Revenue TrackerMedium

  This question evaluates proficiency with data structures and algorithms for hierarchical aggregation and ranking, assessing skills such as maintaining recursive subtree aggregates, handling dynamic inserts, and executing efficient top-k queries; it is in the Coding & Algorithms domain and tests practical application of in-memory data structure design. It is commonly asked to evaluate the ability to design scalable, low-latency in-memory systems that preserve aggregate values across referral trees and support fast query operations while reasoning about time and space complexity trade-offs.

  UberMachine Learning EngineerCoding & AlgorithmsOnsite
• Implement binary search from scratchMedium

  An Uber software engineer onsite coding question asking you to implement binary search on a sorted integer array from scratch, in both iterative and recursive form. It covers plain search, first/last occurrence with duplicates, the insertion-index variant, overflow-safe midpoint computation, loop invariants and correctness, and time/space complexity analysis.

  UberSoftware EngineerCoding & AlgorithmsOnsite
• Implement linear and logistic regressionMedium

  This question evaluates understanding and hands-on implementation of linear and logistic regression, testing competencies in prediction functions, loss formulation, gradient computation, gradient descent training, regularization, and model selection within the Machine Learning domain (supervised learning and statistical modeling).

  UberMachine Learning EngineerMachine LearningTechnical Screen
• Implement rate limiter, top-K, scheduler algorithmsMedium

  This question evaluates proficiency in concurrent programming and thread-safe design, core algorithm implementation (binary search and top-K logic), data structure usage (including doubly-linked-list techniques), and scheduling and ranking reasoning for meeting and resource allocation.

  UberSoftware EngineerCoding & AlgorithmsOnsite
• Implement three interview-style coding tasksHard

  This set of tasks evaluates algorithm and data-structure design skills within the Coding & Algorithms domain, focusing on array windowing and range constraints, dynamic connectivity with component-size maintenance, and time-windowed streaming counters with per-user rate limiting.

  UberSoftware EngineerCoding & AlgorithmsOnsite
• Implement uniform sampling in squaresMedium

  Implement uniform sampling in squares evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

  UberSoftware EngineerCoding & AlgorithmsOnsite
• Implement weighted sampling without replacementMedium

  This question evaluates a candidate's ability to design numerically stable, streaming weighted-sampling methods and tests competencies in randomized algorithms, probability, numerical analysis, and memory/time trade-offs.

  UberData ScientistCoding & AlgorithmsTechnical Screen
• Improve Estimated Time of Arrival for Uber RidersHard

  This interview question evaluates metric design, causal reasoning, experiment setup, diagnostics, SQL/statistical checks, and recommendations in a realistic interview setting. A strong answer for Improve Estimated Time of Arrival for Uber Riders states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

  UberData ScientistAnalytics & ExperimentationTechnical Screen
• Investigate ride declines and test free trialsHard

  This question evaluates proficiency in product analytics, cohort and funnel analysis, retention and supply diagnostics, pricing and subscription economics, and experimentation design.

  UberData ScientistAnalytics & ExperimentationOnsite
• Kth Employee Reached in an Ordered HierarchyMedium

  This problem tests tree traversal techniques, specifically finding the k-th node in an in-order traversal of a binary search tree while handling dynamic updates or specific subtree constraints.

  UberSoftware EngineerCoding & AlgorithmsOnline Assessment
• Last Truck to Leave a One-Dimensional LaneMedium

  Determine the time and ID of the last truck to exit a one-dimensional lane where trucks travel at constant speed and reverse directions upon colliding.

  UberSoftware EngineerCoding & AlgorithmsOnline Assessment
• Maintain the First Value That Appears Exactly OnceHard

  Practice a Uber coding interview problem focused on maintain the first value that appears exactly once. The prompt emphasizes edge cases, clean implementation, and verifiable test behavior without revealing the solution.

  UberSoftware EngineerCoding & AlgorithmsTechnical Screen
• Maximize Minimum Scaled ValueHard

  This problem tests your ability to use binary search on the answer space to solve a constrained resource allocation problem effectively.

  UberSoftware EngineerCoding & AlgorithmsOnline Assessment
• Maximize Throughput and Count Trigger ComponentsMedium

  This problem tests your ability to optimize resource allocation using a greedy strategy and to identify connected components in a grid-based graph using traversal techniques.

  UberSoftware EngineerCoding & AlgorithmsTechnical Screen
• Maximize stock profit with one or two tradesHard

  This question evaluates algorithmic problem-solving skills in array processing and transaction-constrained optimization, exercising greedy and dynamic programming concepts within the Coding & Algorithms domain.

  UberSoftware EngineerCoding & AlgorithmsOnsite
• Maximize the Eligible Carpool GroupMedium

  This problem tests your ability to use a sweep-line algorithm or difference array to find the optimal point to maximize the number of overlapping intervals, subject to specific constraints.

  UberSoftware EngineerCoding & AlgorithmsOnsite
• Maximum Score with Prime JumpsHard

  This problem tests dynamic programming and number theory, specifically the ability to combine linear path traversal with jump-based transitions constrained by prime number properties.

  UberSoftware EngineerCoding & AlgorithmsOnline Assessment
• Measure feature impact with switchback, PSM, and CACEEasy

  This question evaluates proficiency in causal inference and experimental design for product metrics, specifically testing knowledge of switchback experiments, time-series adjustments (seasonality and autocorrelation), propensity score methods for observational comparisons, and complier-average causal effect (LATE/CACE) estimation; it belongs to the Analytics & Experimentation and Data Science domain. It is commonly asked because it probes handling of real-world complications—time and city heterogeneity, non-compliance, and derived-metric inference—and tests both conceptual understanding of causal assumptions and practical application of statistical adjustment and inference.

  UberData ScientistAnalytics & ExperimentationTechnical Screen
• Measure rider incentive causal ROIHard

  This question evaluates a data scientist's competency in causal inference and experimental design, marketplace health metric construction, ROI estimation, and the handling of selection bias, spillover effects, multiple testing, and heterogeneity in two-sided platforms.

  UberData ScientistStatistics & MathTechnical Screen
• Minimum Delivery Cost Between CitiesMedium

  This problem tests your ability to optimize pathfinding costs in a graph where edge weights are determined by a combination of absolute differences and conditional local minimums.

  UberSoftware EngineerCoding & AlgorithmsOnline Assessment
• Minimum Rooms, Merged Busy Blocks and Conflict Handling for Meeting IntervalsMedium

  A multi-part coding question built on the classic meeting-room scheduling problem: find the minimum number of rooms for a set of meetings, merge overlapping meetings into busy blocks, and detect and handle booking conflicts. It tests interval ordering, endpoint conventions, sweep reasoning and efficient lookups.

  UberSoftware EngineerSoftware Engineering FundamentalsTechnical Screen
• Model user-to-resource access permissions in a graph database and migrate to itMedium

  Design how to store and check which people can access which resources using a graph database, including the vertex and edge schema, access-check traversals, and scaling with caching and partitioning. It also covers migrating from the existing database without downtime, testing access modeling, bounded traversals and safe data migration.

  UberSoftware EngineerSystem DesignOnsite
• Move zeros to frontMedium

  This problem tests your ability to manipulate array indices in-place to reorder elements according to a specific condition while maintaining relative stability.

  UberData ScientistCoding & AlgorithmsTechnical Screen
• Navigate urgency, priorities, and conflictHard

  This question evaluates a candidate's ability to manage ambiguity, prioritize competing projects and deadlines, navigate cross-team dependencies, influence stakeholders without formal authority, and quantify outcomes and process improvements.

  UberData ScientistBehavioral & LeadershipTechnical Screen