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Interview Questions
Practice 9403 coding, system design and machine learning questions from 546 companies, sorted by role, topic and interview round. Every question has step-by-step hints, a code runner that supports 8 languages and an AI mentor; members also get the full solution walkthrough.
- 9403
- Questions
- 546
- Companies
- 11
- Topics
- 8
- Languages
Showing 3091–3120 of 9403 results
- DoorDashMediumSoftware EngineerImplement string matching with follow-up
A DoorDash software-engineer coding screen on string matching: implement firstIndex(T, P) in O(|T| + |P|) time and O(|P|) space using KMP, then handle follow-ups on naive vs KMP vs Rabin–Karp, Unicode and very long inputs, edge cases, wildcard ('?'/'*') matching, and simultaneous multi-pattern search via Aho–Corasick. Includes corrected, complete solutions and complexity trade-offs.
Coding & AlgorithmsTechnical Screen - DoorDashMediumSoftware EngineerImplement string-path file system operations
This question evaluates competency in designing data structures for hierarchical string-path file systems, including string parsing, stateful API semantics, validation logic, and efficient lookup/update operations.
Coding & AlgorithmsTechnical Screen - DoorDashMediumData ScientistInvestigate Causes of Cold Food Deliveries and Solutions
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 Investigate Causes of Cold Food Deliveries and Solutions states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Analytics & ExperimentationTechnical Screen - DoorDashMediumData ScientistInvestigate Causes of Cold Meal Deliveries
DoorDash data scientist case on cold meal deliveries, covering lifecycle timestamps, complaint metrics, segmentation, root-cause analysis, dispatch and packaging fixes, A/B testing, and marketplace guardrails.
Analytics & ExperimentationTechnical Screen - DoorDashMediumData ScientistInvestigate Causes of Increased Driver Wait Time
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 Investigate Causes of Increased Driver Wait Time states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Analytics & ExperimentationTechnical Screen - DoorDashHardData ScientistInvestigate Declining Successful Orders
This question tests your ability to decompose a high-level drop in a key business metric into granular segments and formulate testable hypotheses to explain the underlying root causes.
Analytics & ExperimentationTechnical ScreenProduct AnalyticsFunnel AnalysisHypothesis Testing - DoorDashHardData ScientistInvestigate Falling Successful Orders
This question evaluates a data scientist's ability to diagnose a drop in a product metric through anomaly verification, data validity checks, funnel and cohort analysis, causal attribution across marketplace sides (customer, restaurant, delivery), and experiment design.
Analytics & ExperimentationTechnical Screen - DoorDashHardData ScientistInvestigate Falling Successful Orders in LA
This problem tests your ability to decompose a drop in a high-level business metric into granular segments, formulate testable hypotheses, and propose methodologies to identify the root cause.
Analytics & ExperimentationTechnical ScreenRoot Cause AnalysisFunnel AnalyticsMarketplace Dynamics - DoorDashMediumSoftware EngineerInvestigate High Memory Usage
This question evaluates incident-response and operational debugging skills, focusing on diagnosing high memory usage in a distributed microservice architecture that includes caching and third-party integrations.
Software Engineering FundamentalsOnsite - DoorDashMediumData ScientistInvestigate LA Order Drop
This question evaluates marketplace analytics, causal inference, hypothesis-driven investigation, funnel decomposition, and experimentation design skills in a data science context.
Analytics & ExperimentationTechnical Screen - DoorDashEasyProduct AnalystInvestigate LA successful orders drop
This question tests your ability to methodically decompose a performance metric drop, isolate potential root causes using data dimensions, and suggest analytical steps to distinguish between technical issues and marketplace dynamics.
Analytics & ExperimentationTechnical ScreenProduct AnalyticsFunnel AnalysisRoot Cause Analysis - DoorDashMediumData ScientistInvestigate Pop-up Impact on Partner Referral Conversions
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 Investigate Pop-up Impact on Partner Referral Conversions states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Analytics & ExperimentationOnsite - DoorDashMediumSoftware EngineerInvestigate a Surge of Incorrect-Delivery Complaints at Scale
Triage thousands of delivery complaints using rates, joined operational data, focused sampling, mitigation, and evidence of recovery.
Behavioral & LeadershipOnsite - DoorDashMediumSoftware EngineerMake Rider Addition and Dispatch Safe Under Concurrency
Make concurrent rider addition and dispatch safe with atomic availability-to-assignment transitions, idempotent adds, narrow locks, and explicit distributed-state limits.
Software Engineering FundamentalsOnsite - DoorDashMediumSoftware EngineerMake a Courier Pay Workflow Resilient to Downstream Failures
Tests your ability to implement an idempotent, fault-tolerant workflow engine that safely executes financial transactions against an unreliable downstream ledger.
Software Engineering FundamentalsTechnical ScreenDistributed SystemsIdempotencyAPI Design - DoorDashMediumData ScientistMeasure Impact of Merchant Variety on Consumer Experience
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 Measure Impact of Merchant Variety on Consumer Experience states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Analytics & ExperimentationOnsite - DoorDashMediumMachine Learning EngineerMinimize batches and allocate riders by time
This problem tests your ability to optimize resource scheduling by grouping tasks with overlapping time windows into the minimum number of batches, subject to capacity constraints.
Coding & AlgorithmsTechnical ScreenGreedyIntervalsBin Packing - DoorDashMediumData ScientistModel schema and query new-market readiness
This question evaluates SQL-based data manipulation skills including time-series aggregation, cohort analysis, percentile/median calculations, joins between event and reference tables, and deriving operational KPIs for new-market readiness; it targets the Data Manipulation (SQL/Python) domain for a Data Scientist role.
Data Manipulation (SQL/Python)Onsite - DoorDashMediumSoftware EngineerOwn Production Incidents and Validate Large Pipeline Migrations
Plan scalable migration checks, detect silent zero-output failures, and define incident recovery and monitoring ownership without a separate QA team.
Software Engineering FundamentalsOnsite - DoorDashMediumSoftware EngineerPaying Dashers Reliably When the Payment Service Is Unavailable
A system design follow-up about paying delivery drivers when the downstream payment service is unavailable. It tests reasoning about timeouts with unknown outcomes, durable records of amounts owed, retries that must never double-pay, recovery after long outages, reconciliation, and what drivers and operators see while payouts are delayed.
System DesignTechnical Screen - DoorDashMediumSoftware EngineerPooled Rideshare Earnings With Concurrent Rides and Surge
Compute a pooled-ride driver's total earnings where each minute's pay scales with how many riders are currently in the car, and minutes inside non-overlapping surge windows pay double, testing sweep-line interval counting with exact half-open boundaries and 64-bit totals.
Coding & AlgorithmsTechnical Screensweep-lineintervalsarrays - DoorDashHardSoftware EngineerPresent Your Proudest Project
Tests your ability to articulate a high-impact technical project end-to-end, highlighting architectural ownership, difficult trade-offs, rollout execution, and quantifiable business impact.
Behavioral & LeadershipOnsiteBehavioralLeadershipSystem Design - DoorDashHardData ScientistPrioritize projects and manage tight deadlines
This question evaluates prioritization, scope definition, stakeholder leadership, resource and risk management competencies for a Data Scientist in the Behavioral & Leadership category.
Behavioral & LeadershipOnsite - DoorDashMediumSoftware EngineerProcess Orders Through a DAG with Completion and Timeout Refunds
Design order DAG execution with prerequisite state, atomic completion-versus-timeout decisions, idempotent refunds, durable recovery, and accurate status queries.
System DesignOnsite - DoorDashMediumSoftware EngineerProject Deep Dive: Technology Choices, Trade-offs, Hindsight and Working with PMs
A DoorDash project deep dive and hiring manager conversation about a project you are proud of. It probes why you chose your technologies, which alternatives and trade-offs you weighed, the challenges you faced, what you would change, and how you worked with other teams and product managers.
Behavioral & LeadershipOnsite - DoorDashMediumSoftware EngineerProtect SLA and Choose Storage
This question evaluates system design competencies in service reliability and storage architecture, focusing on SLA protection during upstream latency spikes and trade-offs in choosing in-memory caches (e.g., Redis), relational databases, or alternative storage for order and payment state.
System DesignTechnical Screen - DoorDashMediumSoftware EngineerRecover a Project That Has Gone Off Track
This question assesses a candidate's ability to demonstrate leadership, analytical rigor, and project management skills when facing technical or execution failures.
Behavioral & LeadershipTechnical ScreenLeadershipProject ManagementCommunication - DoorDashEasyData ScientistReduce Cold-Food Incidents with Metrics and an Insulated-Bag Experiment
Design an A/B test and metric framework to evaluate whether equipping couriers with insulated bags reduces cold-food complaints while guarding marketplace efficiency.
Analytics & ExperimentationTechnical ScreenExperimentationA/B TestingMetrics Design - DoorDashMediumData ScientistResolve Conflicts and Deliver Results Under Pressure
DoorDash data scientist behavioral prompt on cross-functional disagreement, delivering under limited data or resources, receiving critical feedback, STAR-L storytelling, measurable results, and reflection.
Behavioral & LeadershipOnsite - DoorDashMediumSoftware EngineerResolve Disagreement, Use Feedback, and Grow Engineering Judgment
Discuss technical disagreement, constructive feedback, concrete growth practices, and how varied perspectives contribute to accountable team decisions.
Behavioral & LeadershipOnsite
DoorDash