Katkat

Company

The Trade Desk interview questions

7 practice questions in the style of The Trade Desk's interviews, covering Software Engineering Fundamentals, Behavioral & Leadership, Coding & Algorithms, Machine Learning.

Questions7

4 easy3 medium0 hard

Your progress0/7

The Trade Desk interview questions by the numbers

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Katkat has 7 The Trade Desk interview questions. The largest topics are Coding & Algorithms (43%), Software Engineering Fundamentals (29%) and Behavioral & Leadership (14%). By difficulty: 57% easy and 43% medium. The most common round is Technical Screen (57%). Frequent concepts include Arrays, Logic, Simulation and State Machine.

Difficulty

  • Easy57% · 4
  • Medium43% · 3

Interview rounds

  • Technical Screen57% · 4
  • Online Assessment29% · 2
  • Onsite14% · 1

Roles

  • Software Engineer57% · 4
  • Data Scientist43% · 3

Frequent concepts

  • Arrays14% · 1
  • Logic14% · 1
  • Simulation14% · 1
  • State Machine14% · 1

Showing 1–7 of 7 results

  • Add a click listener to a button evaluates requirements, assumptions, structured reasoning, trade-offs, and verification in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

    The Trade DeskSoftware EngineerSoftware Engineering FundamentalsTechnical Screen
  • This question evaluates communication, decision-making, project execution, technical depth in modeling and evaluation, learning agility, and stakeholder management for a Data Scientist internship within the Behavioral & Leadership category.

    The Trade DeskData ScientistBehavioral & LeadershipTechnical Screen
  • This problem tests your ability to manage state and look-ahead logic when processing a sequence of events (bowling rolls) governed by specific conditional scoring rules.

    The Trade DeskSoftware EngineerCoding & AlgorithmsOnsite
  • This Trade Desk data-science screen asks you to design an end-to-end conversion-rate (CVR) model for real-time bidding (RTB) at a DSP. It covers RTB system roles, label/attribution-window definition, bid-time feature engineering and leakage, logistic-regression vs LightGBM tradeoffs, log-loss training, class-imbalance handling with calibration, PR-AUC vs ROC-AUC evaluation, and latency-aware, safely-deployed production.

    The Trade DeskData ScientistMachine LearningTechnical Screen
  • Evaluates API and in-memory data structure design, search and sorting semantics, user-associated operations, versioning/audit history, data normalization, and edge-case handling within the Software Engineering Fundamentals domain.

    The Trade DeskSoftware EngineerSoftware Engineering FundamentalsOnline Assessment
  • This question evaluates a candidate's ability to implement an in-memory cloud storage system, exercising skills in data structures and stateful API design, string handling and pattern matching, sorting and eviction algorithms, and per-user resource accounting.

    The Trade DeskSoftware EngineerCoding & AlgorithmsOnline Assessment
  • This question evaluates proficiency with piecewise-linear interpolation on strictly increasing (monotonic) arrays, sound handling of out-of-range queries (error, clamp, extrapolate, or None/NaN), and efficient interval search over sorted data with a target of O(log n). It also probes real-world judgment about when each out-of-range policy is appropriate and which non-bisect strategies exist.

    The Trade DeskData ScientistCoding & AlgorithmsTechnical Screen

The Trade Desk interview experiences

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  • A Take-Home Stock-Price API TaskThe Trade Desk · Software Engineer · Take-home Project · Aug 2026

    I am not sure whether this take-home assessment is the same as an online assessment. Implement a single function that returns a list containing every date between first_date and last_date, together with the stock's opening and closing prices for each date. The rough interface was: The output looked roughly like this: All of this information had to be obtained through real HTTP requests. The promp…

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