Uber interview questions

Showing 1–30 of 217 results

• Aligning Two Teams with Conflicting Priorities and Learning from a MistakeMedium

  Two senior behavioral prompts: describe bringing two teams with conflicting priorities into alignment to deliver an important project, and a mistake you made, the feedback you received and how you closed the gap. It assesses cross-team influence, conflict resolution and growth.

  UberSoftware EngineerBehavioral & LeadershipOnsite
• Analyze Cancellation Change with StatisticsMedium

  This question evaluates statistical inference for binary outcomes, regression adjustment for confounding, experiment design and power analysis, and nonparametric uncertainty estimation using bootstrapping, and is targeted at Data Scientist roles within the Statistics & Math domain.

  UberData ScientistStatistics & MathTechnical Screen
• Analyze sales with groupbyEasy

  This question evaluates proficiency in data manipulation and analytics using pandas, specifically the ability to join relational tables and apply groupby aggregations to compute business metrics like total sales, average sales per order, and completion rates.

  UberMachine Learning EngineerCoding & AlgorithmsTechnical Screen
• Answer Common Behavioral QuestionsMedium

  This question assesses the candidate's ability to navigate professional conflict and technical disagreements while maintaining constructive relationships and project momentum.

  UberSoftware EngineerBehavioral & LeadershipOnsite
• Answer Repeated Shortest Increasing-Path QueriesHard

  Preprocess shortest strictly increasing grid paths for repeated target queries, with deterministic BFS ties, predecessor reconstruction, and memory trade-offs.

  UberSoftware EngineerCoding & AlgorithmsOnsite
• Answer leadership questions on tradeoffs and collaborationMedium

  This set of behavioral leadership questions evaluates leadership competencies including trade-off decision-making, mentorship, cross-functional collaboration, roadmap prioritization, and conflict resolution for a Machine Learning Engineer within the Behavioral & Leadership domain, focusing on practical application through recounting real project experiences. These prompts are commonly asked to probe both conceptual understanding of trade-offs and organizational dynamics and the practical application of influence, communication, and judgment when aligning stakeholders and prioritizing work.

  UberMachine Learning EngineerBehavioral & LeadershipOnsite
• Apply instrumental variables under interferenceHard

  This question evaluates understanding of causal inference with instrumental variables in the presence of interference, testing skills in defining units and aggregation levels for market‑level spillovers, articulating IV assumptions (relevance, exclusion restriction, independence, monotonicity), and formulating estimation frameworks such as two‑stage least squares. Commonly asked in Statistics & Math interviews for data scientist roles because networked marketplaces invalidate simple A/B tests, it sits in the econometrics/causal inference domain and primarily assesses practical application of IV methods while requiring conceptual understanding of identification, robustness diagnostics, and sensitivity analysis.

  UberData ScientistStatistics & MathTechnical Screen
• Assign Meetings to the Minimum Number of RoomsMedium

  Assign meetings to the minimum number of rooms using deterministic room ID allocation, returning the room assigned to each meeting in original input order.

  UberSoftware EngineerCoding & AlgorithmsOnsite
• Behavioral: your most complex project, a conflict you resolved, and a failureMedium

  Three hiring-manager behavioral questions: describe your most complex project, a conflict you resolved, and a failure you owned. Answers are judged on STAR structure, personal ownership, concrete and measurable results, a fair account of other people's views, and lessons that were actually applied later.

  UberSoftware EngineerBehavioral & LeadershipOnsite
• Bracket substrings matching any patternMedium

  This problem tests your ability to efficiently match and replace substrings based on a set of predefined patterns, prioritizing matches based on position and length.

  UberSoftware EngineerCoding & AlgorithmsTechnical Screen
• Build Quadtree and Find Grid WordsHard

  This problem tests your ability to implement a spatial partitioning data structure (Quadtree) for a grid and perform recursive searches to locate words within that grid efficiently.

  UberSoftware EngineerCoding & AlgorithmsOnsite
• Build a Quadtree and Analyze a GraphMedium

  This question evaluates skills in spatial data structures and recursive tree construction (building a quadtree) as well as graph analysis using traversal and cycle/safety detection to identify nodes that necessarily reach terminal nodes.

  UberSoftware EngineerCoding & AlgorithmsTechnical Screen
• Build cold-start restaurant ratingsMedium

  This problem tests the ability to design an end-to-end machine learning system for predicting restaurant ratings when historical user-item interactions are scarce, focusing on feature engineering, model selection, and bias mitigation.

  UberData ScientistMachine LearningTechnical Screen
• Can one car serve all riders?Medium

  This problem tests your ability to determine if a single resource (a car) can accommodate a series of scheduled tasks without overlap, requiring efficient sorting and comparison techniques.

  UberData ScientistCoding & AlgorithmsTechnical Screen
• Check feasibility of AI course scheduleHard

  This question evaluates competency in analyzing directed graphs and dependency resolution, focusing on cycle detection and the feasibility of ordering prerequisites for course completion.

  UberSoftware EngineerCoding & AlgorithmsOnsite
• Check if each prefix forms 1..k permutationHard

  This question evaluates algorithmic thinking and understanding of permutations and prefix invariants, measuring the ability to recognize when the first k elements of a permutation can form the set {1..k}.

  UberSoftware EngineerCoding & AlgorithmsOnline Assessment
• Choose K pickup locations minimizing L1 distanceMedium

  This question evaluates facility-location and spatial optimization skills under the Manhattan (L1) metric, testing algorithm design, combinatorial optimization, and handling geometric data.

  UberMachine Learning EngineerCoding & AlgorithmsOnsite
• Compare Paxos and RaftHard

  This question evaluates understanding of distributed consensus protocols, replicated logs, linearizability, fault tolerance, and operational concerns such as leader election, quorum semantics, log replication, membership changes, and failure recovery.

  UberSoftware EngineerSystem DesignOnsite
• Compare Two Coin ProportionsMedium

  This question evaluates proficiency in statistical inference for proportions, including hypothesis formulation, comparison of two independent samples, confidence interval interpretation, and interpretation of p-values and sampling variability.

  UberData ScientistStatistics & MathTechnical Screen
• Compute A/B sample size under clusteringHard

  This question evaluates competency in experimental design and statistical inference for A/B testing, specifically sample size calculation for two-sample proportions with unequal allocation, clustering effects (ICC and design effect), and adjustments for bot removal and data-quality attrition.

  UberData ScientistStatistics & MathTechnical Screen
• Compute CDF from a PDF FunctionMedium

  This problem tests your understanding of numerical integration techniques (specifically the trapezoidal rule) and your ability to implement a functional mapping of a continuous probability density function (PDF) into a discrete cumulative distribution function (CDF).

  UberData ScientistCoding & AlgorithmsTechnical Screen
• Compute ETA shift and conversion upliftMedium

  This question evaluates proficiency in SQL and Python for time‑series data manipulation and experimental analysis, covering window functions (7‑day percentile_cont medians), date spines and timezone‑aware timestamp truncation, conversion-rate aggregation, difference‑in‑differences uplift estimation, and CUPED adjustment with cluster‑robust standard errors. It is commonly asked to assess practical data engineering and applied statistics skills in the Data Manipulation (SQL/Python) domain, testing applied implementation and causal inference ability rather than only conceptual understanding.

  UberData ScientistData Manipulation (SQL/Python)Technical Screen
• Compute currency conversion via graph searchMedium

  This question evaluates graph modeling and pathfinding with weighted edges, numerical reasoning about multiplicative rates and floating-point precision, and the ability to analyze algorithmic time and space complexity.

  UberMachine Learning EngineerCoding & AlgorithmsTechnical Screen
• Compute final prices with next smaller discountMedium

  This question evaluates array-processing and algorithmic problem-solving skills, focusing on reasoning about subsequent elements to compute element-wise discounts under input constraints.

  UberSoftware EngineerCoding & AlgorithmsOnline Assessment
• Compute maximum concurrent trips from intervalsMedium

  This question evaluates a candidate's skill in designing efficient algorithms for interval overlap counting, including event ordering, handling half-open interval edge cases, and reasoning about concurrent activity timing.

  UberData ScientistCoding & AlgorithmsTechnical Screen
• Compute minimal time to finish dependent tasksMedium

  This question evaluates understanding of graph algorithms and scheduling, specifically reasoning about task dependencies, parallel execution, and cycle detection in directed graphs.

  UberMachine Learning EngineerCoding & AlgorithmsOnsite
• Compute outer boundary of an N-ary treeMedium

  This question evaluates proficiency in tree data structures and algorithm design, focusing on traversal and boundary extraction in ordered N-ary trees while requiring time and space complexity analysis.

  UberSoftware EngineerCoding & AlgorithmsTechnical Screen
• Compute square root to 1 decimalMedium

  This question evaluates a candidate's understanding of numerical methods, floating-point precision, and implementation of approximate functions when producing a square root rounded to one decimal place.

  UberData ScientistCoding & AlgorithmsTechnical Screen
• Compute sums and maximum path in a treeMedium

  This problem tests your ability to perform post-order tree traversals to calculate subtree metrics and solve optimization problems involving paths that can span across parent-child boundaries.

  UberSoftware EngineerCoding & AlgorithmsOnline Assessment
• Compute time for virus to infect gridMedium

  This question tests the ability to model state propagation in a 2D grid using a Breadth-First Search (BFS) approach to determine the minimum time required for a condition to cover all cells.

  UberSoftware EngineerCoding & AlgorithmsTechnical Screen