Katkat

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Intuit interview questions

34 practice questions in the style of Intuit's interviews, covering Coding & Algorithms, ML System Design, Software Engineering Fundamentals, Analytics & Experimentation, Machine Learning, Data Manipulation (SQL/Python), System Design, Behavioral & Leadership.

Questions34

9 easy24 medium1 hard

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Intuit interview questions by the numbers

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Katkat has 34 Intuit interview questions. The largest topics are Coding & Algorithms (26%), Data Manipulation (SQL/Python) (18%) and Machine Learning (15%). By difficulty: 26% easy, 71% medium and 3% hard. The most common round is Technical Screen (62%). Frequent concepts include System Design, Algorithms, Cohort Analysis and Math.

Difficulty

  • Easy26% · 9
  • Medium71% · 24
  • Hard3% · 1

Interview rounds

  • Technical Screen62% · 21
  • Onsite18% · 6
  • Online Assessment15% · 5
  • HR Screen6% · 2

Roles

  • Software Engineer56% · 19
  • Data Scientist29% · 10
  • Product Analyst6% · 2
  • Staff Software Engineer6% · 2
  • Machine Learning Engineer3% · 1

Frequent concepts

  • System Design9% · 3
  • Algorithms6% · 2
  • Cohort Analysis6% · 2
  • Math6% · 2
  • Object-Oriented Design6% · 2
  • Retention6% · 2

Showing 1–30 of 34 results

  • This problem tests your ability to handle array-based arithmetic and carry-over logic, specifically focusing on edge cases like digit overflow and resizing the array.

    IntuitSoftware EngineerCoding & AlgorithmsTechnical Screen
  • Add an LLM-powered recommendation endpoint to an existing backend service. Design the request flow, write the actual prompt and its structured output format, and discuss retrieval-augmented generation, hallucination, prompt injection, and how to evaluate and monitor the feature.

    IntuitSoftware EngineerML System DesignOnsite
  • This question evaluates a candidate's proficiency with SQL aggregation, grouping, window functions, string aggregation, and normalization techniques for summarizing transactional records by status and failure reasons.

    IntuitSoftware EngineerSoftware Engineering FundamentalsOnline Assessment
  • This problem tests your ability to aggregate user activity data to calculate 30-day retention rates, requiring joins, date arithmetic, and windowing functions.

    IntuitData ScientistAnalytics & ExperimentationTechnical Screen
  • This problem tests your ability to design an end-to-end predictive modeling pipeline for tax-related data, focusing on feature engineering, handling imbalanced datasets, and selecting appropriate evaluation metrics.

    IntuitData ScientistMachine LearningOnsite
  • This problem tests your ability to manipulate time-series data to calculate cohort-based user retention rates while handling data censoring constraints.

    IntuitData ScientistAnalytics & ExperimentationTechnical Screen
  • This question evaluates a candidate's ability to compute subscription churn and revenue retention metrics from monthly snapshots, exercising SQL data-manipulation competencies such as handling missing or null MRR values, deduplicating snapshot loads, joining across months, and aggregating MRR changes.

    IntuitData ScientistData Manipulation (SQL/Python)HR Screen
  • This question evaluates proficiency in SQL time-series aggregation and cohort identification, including generating a month spine, computing year-over-year deltas, handling nulls and division-by-zero, and identifying partial months via a data watermark.

    IntuitData ScientistData Manipulation (SQL/Python)Technical Screen
  • This question tests the ability to design an end-to-end recommendation architecture, focusing on the trade-offs between relevance, latency, and data privacy in a financial context.

    IntuitSoftware EngineerML System DesignTechnical Screen
  • This question tests the ability to design an end-to-end machine learning system that predicts future best-sellers and serves real-time recommendations, balancing model accuracy, batch processing, and serving latency.

    IntuitSoftware EngineerML System DesignTechnical Screen
  • Design a windowed rate limiter that admits five requests per window, prioritizing VIP requests while guaranteeing non-preemption, idempotency, and starvation prevention for regular users.

    IntuitStaff Software EngineerSoftware Engineering FundamentalsTechnical Screen
  • This question evaluates a candidate's competency in experiment design, causal inference, impact sizing, metric framework development, and statistical analysis in the context of a pricing page redesign that adds an annual subscription option.

    IntuitData ScientistAnalytics & ExperimentationTechnical Screen
  • This question evaluates a candidate's competence in designing robust ETL pipelines, covering idempotent processing, handling late-arriving streaming subscription events, SCD Type 2 slowly changing dimensions, incremental backfills, data quality checks, upsert/merge semantics, and metric versioning.

    IntuitData ScientistData Manipulation (SQL/Python)HR Screen
  • This Intuit data scientist machine learning screen evaluates feature engineering from address/ZIP data, joining external census-style datasets, high-cardinality encoding, and missing-ZIP imputation. It also tests awareness of fairness, privacy, leakage, and how to validate whether geographic features actually improve a model.

    IntuitData ScientistMachine LearningTechnical Screen
  • This question evaluates competency with SQL anti-joins, join semantics, deduplication, and correct pre-aggregation filtering to prevent excluded entities from affecting aggregated monthly and year-over-year metrics; it is categorized as Data Manipulation (SQL/Python) for a Data Scientist role.

    IntuitData ScientistData Manipulation (SQL/Python)Technical Screen
  • Staff-level backend interview discussion on AI fluency. Explain what a large language model is, contrast AI-native products with conventional apps that add AI features, describe how you use AI tools in daily engineering work, and weigh the main dangers of AI with concrete mitigations.

    IntuitSoftware EngineerMachine LearningTechnical Screen
  • This question evaluates a candidate's ability to analyze multistep funnel metrics, handle highly skewed traffic across many access points, and prioritize insights from sparse or long-tail data, testing competencies in product analytics and measurement.

    IntuitProduct AnalystAnalytics & ExperimentationOnsite
  • This question evaluates understanding of graph traversal and shortest-path computation, including modeling business relationships as undirected graphs and interpreting degrees of separation on the shortest path.

    IntuitSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This problem tests your ability to navigate the file system using command-line utilities and process streaming data to identify files based on size metadata.

    IntuitSoftware EngineerSoftware Engineering FundamentalsOnline Assessment
  • This question evaluates proficiency in text parsing, tokenization, and numeric comparison applied to command-line style output, emphasizing robust handling of varied input formats and edge cases.

    IntuitSoftware EngineerCoding & AlgorithmsOnline Assessment
  • This question evaluates a product analyst's machine learning competencies in diagnosing data quality issues, handling feature availability and training-serving skew, and interpreting counterintuitive correlations, testing both conceptual understanding and practical application for model development and deployment.

    IntuitProduct AnalystMachine LearningOnsite
  • This question evaluates understanding of cache eviction policies (LRU and LFU), frequency tracking, and the design of data structures that support efficient get/put operations while meeting time and space complexity constraints.

    IntuitSoftware EngineerCoding & AlgorithmsTechnical Screen
  • Implement a field-level access control engine that redacts sensitive attributes from user profile records based on viewer permissions, context, and ownership relationships.

    IntuitStaff Software EngineerSoftware Engineering FundamentalsTechnical Screen
  • This problem tests your ability to perform manual addition on an array representing a large integer, specifically handling carry propagation and dynamic resizing when the integer overflows its current digit count.

    IntuitSoftware EngineerCoding & AlgorithmsTechnical Screen
  • Find each employee’s longest meeting-free business-hours interval using clipped attendance, merged overlaps, complete day coverage, and SQL window logic.

    IntuitMachine Learning EngineerData Manipulation (SQL/Python)Technical Screen
  • This question evaluates data manipulation and aggregation skills, specifically computing distinct user counts and revenue aggregates and reshaping results by platform; it is in the Data Manipulation (SQL/Python) domain and assesses practical application rather than purely conceptual understanding.

    IntuitData ScientistData Manipulation (SQL/Python)Technical Screen
  • This problem tests your ability to reconstruct a valid topological ordering (parent-before-child) from a parent-child relationship array while maintaining lexicographical minimality.

    IntuitSoftware EngineerCoding & AlgorithmsOnline Assessment
  • System design deep dive on scaling a service built earlier in the same interview loop. Compare schema options, extend the data model for reviews, ratings, and keyword search, and reason about query performance, indexing, pagination, and when a dedicated search engine is worth adding.

    IntuitSoftware EngineerSystem DesignOnsite
  • This question evaluates competencies in string algorithms (word segmentation and palindrome validation), data structures and complexity analysis, and practical frontend React implementation with performance considerations.

    IntuitSoftware EngineerCoding & AlgorithmsTechnical Screen
  • Behavioral prompts from a staff software engineer loop: give a short slide presentation on your background, interests, and proudest project, then answer what excites you at work and what your superpowers are. It tests storytelling, ownership, staff-level scope, and self-awareness.

    IntuitSoftware EngineerBehavioral & LeadershipOnsite

Intuit interview experiences

All 6 →
  • Measuring Meeting-Free Work TimeIntuit · Machine Learning Engineer · Technical Screen · Sep 2026

    The report presents an Intuit AI Science technical-screen exercise reconstructed from images. The task uses a year of company meeting records to assess how much uninterrupted coding time employees have during business hours. Each attendance record identifies an employee and a meeting, together with joining and leaving times. Candidates are asked to determine the longest available interval for eac…

  • Two Long Screens and a Final-Round RejectionIntuit · Staff Software Engineer · Senior+ · Onsite · Aug 2026
    Rejected

    Intuit's interview process had two rounds. The process was long, but HR was patient. The final round was a big production too. First round: Coding The interviewer was very nice and kept encouraging me. The first coding problem was to design a rate limiter. Requirement: design a rate limiter that allows five people through during each time period. Then the design was extended: when VIP users arriv…

  • Intuit Software Engineer interviewIntuit · Software Engineer · Technical Screen · Jul 2026

    The recruiter screen began casually with background and fit questions. They also asked for my views on AI, which felt more like checking my perspective than testing technical knowledge. That tone did not hold in every recruiter interaction. One recruiter became defensive when I was candid about my leveling expectations, and the exchange turned frustrating. In another recruiter-led rejection, the…

  • Laid Off, Craft Demo and an AI Round, Then an OfferIntuit · Software Engineer · Senior+ · Onsite · Dec 2025
    Offer

    This is about my loop for a Staff Software Engineer opening at Intuit, based in Mountain View, CA. I sent out a few online applications, and a recruiter then contacted me. Background I'm based in the US and did my master's here, after arriving in 2013. Meta let me go in September 2025. Before that I put in 3.5 years at AWS, where I mostly did backend work for AWS services. After that came 6 years…

  • TurboTax Take-Home, Growth Team Onsite, and a Slow Recruiter ProcessIntuit · Data Scientist · Onsite · Oct 2025

    First there was a TurboTax home assignment, then a 45-minute presentation plus Q&A. In this part they ask about the recommendations you make based on the data, whether your assumptions are reasonable, and what other data you could look at. I remember there being a question like that, and I didn't have a good answer at the time. The task was predicting whether tax filing succeeds or not, and there…

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