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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
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- 546
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- 11
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Showing 3511–3540 of 9403 results
- GoogleEasySoftware EngineerCount Rectangle Coverage on a Grid
Implement an algorithm to compute cell-by-cell coverage counts for an n x n grid given multiple inclusive rectangular regions.
Coding & AlgorithmsOnsitematrixprefix-sumdifference-array - GoogleMediumSoftware EngineerCount Up-Right/Right/Down-Right Grid Paths Through Ordered Checkpoints
Count the paths across an n by m grid from the bottom-left to the bottom-right cell when each move goes up-right, right or down-right, optionally passing through checkpoints in a required order, modulo a large prime. It tests column-by-column dynamic programming and reducing memory use.
Coding & AlgorithmsOnsite - GoogleEasyData ScientistCount super-streak segments in an event stream
Count super-streak segments in a time-ordered event stream with an O(n) scan. The solution explains maximal segment boundaries, inclusive gap handling, duration and count checks, edge cases, streaming behavior, and changing-threshold follow-ups.
Coding & AlgorithmsTechnical Screen - GoogleMediumSoftware EngineerCount user sessions from logs
This question evaluates a candidate's ability to parse and process large-scale event logs, perform sessionization based on time gaps, handle out-of-order records and memory constraints, and reason about time and space complexity and optimization strategies in the Coding & Algorithms domain.
Coding & AlgorithmsOnsite - GoogleMediumData ScientistDecide between two vendors under constraints
This question evaluates a candidate's competency in decision modeling and cost‑sensitive machine learning, including causal inference for selection bias, propensity estimation, constrained optimization for capacity and SLA trade‑offs, and offline/online evaluation in the Machine Learning domain for a Data Scientist role.
Machine LearningOnsite - GoogleMediumSoftware EngineerDecide string transform with directional tokens and walls
Decide string transform with directional tokens and walls 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.
Coding & AlgorithmsTechnical Screen - GoogleMediumSoftware EngineerDecompress encoded string with nested repeats
This question tests the ability to handle nested structures using recursion or a stack-based approach to expand string patterns based on repetition factors.
Coding & AlgorithmsOnsiteStackRecursionString Manipulation - GoogleMediumSoftware EngineerDeduplicate and Order Batch and Streaming Logs
Design both a batch algorithm and a streaming processor to deduplicate and chronologically order log records under different resolution policies, accounting for out-of-order delivery, late data, and bounded memory.
Software Engineering FundamentalsOnsiteStreamingDeduplicationData Structures - GoogleMediumData ScientistDeduplicate events and rank products with SQL
This question evaluates proficiency in SQL data manipulation and analytical querying—specifically deduplication using idempotency keys, window functions/CTEs for ranking, distinct aggregation by date, timestamp tie-breaking, and awareness of indexing and scalability trade-offs in large tables; the domain is Data Manipulation (SQL/Python).
Data Manipulation (SQL/Python)Technical Screen - GoogleHardSoftware EngineerDefend the Trade-Offs in One Project
This question assesses a candidate's ability to articulate the engineering rationale behind technical decisions, balancing trade-offs against project constraints and evolving requirements.
Behavioral & LeadershipTechnical ScreenBehavioralSystem DesignEngineering Leadership - GoogleHardData ScientistDefine and apply Gmail user segments
A Google data scientist analytics screen: propose actionable Gmail user segments from behavioral metadata, validate their stability and separability over eight weeks, design targeted interventions with metrics and guardrails, and run a privacy-aware experiment to measure per-segment lift. Covers segmentation axes, validation metrics, k-anonymity and differential privacy, CUPED, and RICE roadmap prioritization.
Analytics & ExperimentationTechnical Screen - GoogleMediumData ScientistDemonstrate leadership in data ambiguity
This question evaluates leadership in data ambiguity, assessing competencies in diagnosing underperforming metrics or models, articulating quantified trade-offs, influencing cross-functional stakeholders with data and experiments, and designing operational safeguards and accountability mechanisms.
Behavioral & LeadershipOnsite - GoogleMediumData ScientistDemonstrate stakeholder communication and influence
This question evaluates a candidate's stakeholder communication and influence using data, specifically assessing the ability to present analysis to non-technical partners, manage pushback, make trade-offs, and demonstrate measurable outcomes in a cross-functional decision context for a Data Scientist role.
Behavioral & LeadershipTechnical Screen - GoogleMediumSoftware EngineerDependency-Safe Deletion Order
Tests directed graph modeling, cycle detection, and Kahn's algorithm using a min-heap to produce a lexicographically smallest topological sort.
Coding & AlgorithmsOnsiteTopological SortHeapGraph - GoogleMediumData ScientistDerive MLEs and conditional Normal distributions
This question evaluates proficiency in parametric inference and probability theory, specifically maximum likelihood estimation, bias of estimators, and conditioning in univariate and bivariate Normal distributions including constrained estimation of parameters.
Statistics & MathTechnical Screen - GoogleMediumSoftware EngineerDescribe Key Behavioral Examples
This question evaluates interpersonal and leadership competencies—including communication, conflict resolution, teamwork, accountability, problem-solving, and adaptability—by eliciting concrete behavioral examples from past internships or projects.
Behavioral & LeadershipTechnical Screen - GoogleMediumData ScientistDescribe Overcoming Challenges and Persuading Non-Data Colleagues
Evaluates behavioral interview storytelling for persuading non-data colleagues and resolving workplace challenges. Strong answers use STAR, translate analysis into business terms, handle objections, show collaboration, quantify outcomes, and reflect on lessons learned.
Behavioral & LeadershipTechnical Screen - GoogleMediumData ScientistDescribe Your Research and Cross-Functional Collaboration Experience
Evaluates behavioral storytelling for research rigor and cross-functional collaboration in data science. Strong answers explain problem framing, methodology, validation, stakeholder alignment, impact, and limitations.
Behavioral & LeadershipTechnical Screen - GoogleMediumSoftware EngineerDescribe a Failure and the Change It Prompted
This behavioral interview question evaluates a candidate's self-awareness, accountability, and capacity to convert a significant technical or project setback into enduring operational or personal improvements.
Behavioral & LeadershipOnsiteBehavioralLeadershipPost-Mortem - GoogleEasyData ScientistDescribe a challenging project and how you succeeded
This question evaluates a data scientist's ownership, technical depth in research and modeling, decision-making under constraints, stakeholder management, measurable impact orientation, and reflective learning, and it is categorized under Behavioral & Leadership for Data Scientist roles.
Behavioral & LeadershipHR Screen - GoogleMediumSoftware EngineerDescribe a challenging recent project
This question evaluates leadership, communication, problem‑solving, technical ownership, and the ability to describe trade‑offs, diagnostics, measurable impact, and lessons learned within a software engineering project.
Behavioral & LeadershipOnsite - GoogleMediumSoftware EngineerDescribe a conflict with a colleague
This question evaluates a candidate's interpersonal conflict-resolution, communication, and leadership competencies within software engineering teams, including stakeholder management and accountability.
Behavioral & LeadershipOnsite - GoogleMediumSoftware EngineerDescribe a major challenge you faced
This question evaluates a candidate's behavioral and leadership competencies, including problem-solving, resilience, ownership, communication, and teamwork within academic, internship, or professional technical projects.
Behavioral & LeadershipOnsite - GoogleMediumData EngineerDescribe building and improving a dashboard
Prepare a Google Data Engineer behavioral answer about building and improving a stakeholder dashboard. The solution covers business goals, KPI design, data validation, BI tooling, anomaly detection, root-cause analysis, feedback handling, and measurable impact.
Behavioral & LeadershipTechnical Screen - GoogleHardMachine Learning EngineerDescribe conflict and failure using STAR framework
This question evaluates interpersonal and leadership competencies such as conflict resolution, accountability, communication, and reflective learning, along with proficiency in structuring responses using the STAR behavioral framework.
Behavioral & LeadershipOnsite - GoogleEasySoftware EngineerDescribe conflict resolution and stakeholder management
This question evaluates a candidate's conflict-resolution and stakeholder-management competencies, including mediation, expectation management, and clear communication when navigating disagreements among peers, managers, and cross-functional partners.
Behavioral & LeadershipOnsite - GoogleEasySoftware EngineerDescribe conflict, ambiguity, and process improvement
This question evaluates interpersonal and leadership competencies for a Software Engineer role—specifically conflict resolution, handling ambiguity, process improvement, cross-functional collaboration, and the ability to articulate technical decisions.
Behavioral & LeadershipOnsite - GoogleMediumMachine Learning EngineerDescribe leadership under changing priorities
This question evaluates leadership, ownership, prioritization, communication, and adaptability skills within the Behavioral & Leadership domain for a Machine Learning Engineer role.
Behavioral & LeadershipTechnical Screen - GoogleMediumSoftware EngineerDescribe manager and cross-team communication
This question evaluates cross-functional communication, stakeholder management, expectation-setting, and risk escalation competencies in an engineering context.
Behavioral & LeadershipOnsite - GoogleMediumSoftware EngineerDescribe teamwork and personal achievements
This question evaluates teamwork, leadership, problem-solving, communication, and self-awareness by probing examples of helping an underperforming teammate, managing challenging projects, and describing personal achievements.
Behavioral & LeadershipTechnical Screen
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