Uber interview questions

Showing 91–120 of 217 results

• Design real-time driver heatmap systemHard

  This question evaluates a candidate's ability to design real-time distributed systems for geospatial aggregation, covering skills in spatial partitioning, high-throughput streaming ingestion, low-latency cell counting, WebSocket-based client updates, and top-K ranking within a fault-tolerant multi-region architecture.

  UberSoftware EngineerSystem DesignOnsite
• Design real-time grid ETA for driversHard

  This question evaluates a candidate's competency in real-time ML system design, covering streaming data ingestion, GPS noise handling and denoising, online feature computation, low-latency model serving, and operational monitoring.

  UberMachine Learning EngineerML System DesignOnsite
• Design the Data Flow Behind a Food Delivery App's Restaurant ListHard

  A system design interview question asking you to design the data flow behind a food delivery app's restaurant list for a customer's delivery address. It tests geographic indexing of delivery areas, propagating restaurant status and delivery-time changes, read-path latency, caching, and freshness trade-offs.

  UberSoftware EngineerSystem DesignOnsite
• Design top-K frequency structureMedium

  This question evaluates ability to design efficient in-memory data structures for frequency tracking, including handling recency-based tie-breaking, memory bounds under churn, and concurrency implications.

  UberSoftware EngineerCoding & AlgorithmsOnsite
• Design top-K tracker with linked listsMedium

  Design top-K tracker with linked lists 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
• Determine Sample Size for Promotion Campaign A/B TestMedium

  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 Determine Sample Size for Promotion Campaign A/B Test states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

  UberData ScientistAnalytics & ExperimentationTechnical Screen
• Determine Whether a Word Exists in a Character GridHard

  Practice a Uber coding interview problem focused on determine whether a word exists in a character grid. The prompt emphasizes edge cases, clean implementation, and verifiable test behavior without revealing the solution.

  UberSoftware EngineerCoding & AlgorithmsTechnical Screen
• Determine balanced k values in a permutationMedium

  This question evaluates algorithmic reasoning about permutations and contiguous subarray properties, testing skills in array manipulation, positional reasoning, combinatorial insight, and complexity-aware algorithm design within the Coding & Algorithms domain.

  UberSoftware EngineerCoding & AlgorithmsOnline Assessment
• Develop test plan and TDD for word searchMedium

  This question evaluates a candidate's competency in designing comprehensive test plans and test-driven development workflows for grid-based word search algorithms, covering edge-case identification, input normalization, path validity, and performance/stress considerations within software testing and algorithmic reasoning.

  UberSoftware EngineerSoftware Engineering FundamentalsTechnical Screen
• Encode an N-ary tree as a string and decode it back to the identical treeMedium

  Design a string format for rooted N-ary trees and implement serialize and deserialize so the decoded tree has the same values, shape and child order. It tests unambiguous encoding of variable child counts, linear-time parsing, iterative handling of very deep trees, and validation of malformed input.

  UberSoftware EngineerSoftware Engineering FundamentalsOnsite
• Evaluate ETA Impact on ConversionMedium

  This question evaluates a data scientist's skills in causal inference, experimental design, and marketplace analytics, including understanding of confounding, selection bias, interference, and the distinction between correlation and causation.

  UberData ScientistAnalytics & ExperimentationTechnical Screen
• Evaluate Marketplace ChangesMedium

  This problem tests your ability to design an A/B test for a two-sided marketplace, focusing on network effects, metric selection, and identifying potential interference between treatment and control groups.

  UberData ScientistAnalytics & ExperimentationOnsite
• Evaluate Promotions for Uber Eats UsersMedium

  This question tests the ability to design an A/B test for promotions in a two-sided marketplace, focusing on identifying interference (network effects) and selecting appropriate metrics to measure causal impact.

  UberData ScientistMachine LearningTechnical Screen
• Evaluate Rider-Incentive Program Impact with Key MetricsMedium

  Uber data scientist analytics prompt on evaluating a rider-incentive program, covering experiment design, rider and driver metrics, matching quality, ROI, marketplace externalities, spillovers, and guardrails.

  UberData ScientistAnalytics & ExperimentationTechnical Screen
• Evaluate UberEATS priority delivery and membershipMedium

  This question tests the ability to design an experiment for a marketplace feature and evaluate its impact on key business metrics like conversion, frequency, and total contribution margin.

  UberData ScientistAnalytics & ExperimentationTechnical Screen
• Evaluate a cold-start rating launchMedium

  This question tests the ability to design an evaluation framework for a new feature in a two-sided marketplace while accounting for spillover effects and metrics that represent different stakeholder interests.

  UberData ScientistAnalytics & ExperimentationTechnical Screen
• Evaluate an Arithmetic ExpressionMedium

  This problem tests your ability to parse and evaluate mathematical expressions involving integers, addition, subtraction, multiplication, division, and parentheses using stacks or recursion.

  UberSoftware EngineerCoding & AlgorithmsOnsite
• Evaluate business value of lower ETAMedium

  This question tests the ability to design an experiment that isolates the causal impact of reduced ETA on user retention and to translate these metrics into business value.

  UberData ScientistAnalytics & ExperimentationTechnical Screen
• Evaluate impact without randomized experimentsHard

  This question evaluates a data scientist's competence in causal inference and identification strategies for estimating promotion effects from observational longitudinal data, emphasizing challenges such as staggered rollout, interference (spillovers), seasonality, and uncertainty quantification.

  UberData ScientistAnalytics & ExperimentationTechnical Screen
• Evaluate marketplace interventionsMedium

  This question tests the ability to design an experimentation framework for a two-sided marketplace, specifically addressing interference between supply and demand and selecting appropriate success metrics.

  UberData ScientistAnalytics & ExperimentationOnsite
• Explain and test completion-rate gapsEasy

  This question evaluates understanding of causal inference, product-metrics analysis, experimental design, and statistical hypothesis testing (including two-sample t-tests) as applied to operational problems in a marketplace.

  UberMachine Learning EngineerMachine LearningTechnical Screen
• Explain and validate A/B test assumptionsHard

  This question evaluates proficiency in experimental design, causal inference, and statistical diagnostics for A/B testing, covering competencies such as randomization integrity, SUTVA/interference, noncompliance, time-varying effects, metric missingness, sequential testing, and heterogeneous treatment effects.

  UberData ScientistAnalytics & ExperimentationTechnical Screen
• Find Any Available Meeting RoomMedium

  This question evaluates a candidate's competence in handling interval-based scheduling problems, specifically managing interval data and performing efficient searches within sorted bookings to detect potential overlaps.

  UberSoftware EngineerCoding & AlgorithmsOnsite
• Find Earliest Column With OneEasy

  This question tests the ability to optimize searches in a sorted binary matrix by minimizing expensive API calls through efficient traversal techniques.

  UberSoftware EngineerCoding & AlgorithmsTechnical Screen
• Find Earliest Full Connectivity TimestampMedium

  This question evaluates understanding of graph connectivity and temporal event processing, examining how pairwise interactions over time can merge components into a single connected set.

  UberSoftware EngineerCoding & AlgorithmsTechnical Screen
• Find Kth Smallest in BSTMedium

  This question evaluates understanding of binary search tree properties, ordered data retrieval, and algorithmic efficiency in locating the k-th smallest element.

  UberSoftware EngineerCoding & AlgorithmsTechnical Screen
• Find Robots by Nearest-Blocker DistancesHard

  Implement an algorithm to identify all robots in a grid whose four-directional distances to the nearest obstacle or grid boundary match a target query.

  UberMachine Learning EngineerCoding & AlgorithmsTechnical Screen
• Find a Black-Box Convex Function MinimumMedium

  This question evaluates proficiency in zero-order optimization and algorithm design, focusing on reasoning about convexity and unimodality when only function evaluations are available.

  UberMachine Learning EngineerCoding & AlgorithmsTechnical Screen
• Find a Bounded Subarray and Largest SquareMedium

  This question evaluates array manipulation and algorithmic problem-solving skills across two tasks: enforcing bounded value ranges within contiguous subarrays and identifying largest uniform square regions in binary matrices, exercising concepts such as range-tracking, efficient data structures, and dynamic programming.

  UberSoftware EngineerCoding & AlgorithmsOnsite
• Find a Lexicographically Optimal Robot Path with Charging CellsMedium

  Find a path in a grid from start to target that lexicographically minimizes charging stations used, peak battery segment length, total moves, and breaks ties by flattened cell indices.

  UberSoftware EngineerCoding & AlgorithmsTechnical Screen