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NumPy test for hiring

Check practical NumPy skills with short code questions built around everyday numerical data tasks.

10 menit
16 pertanyaan
Intermediate
Multiple choice
Questions in Inggris
Phone and desktop

Use this test free See the question formats

Jawaban singkat

The NumPy skills test is a 10-minute, 16-question check for intermediate roles working with numerical data in Python. Multiple-choice questions assess creating and manipulating arrays, plus selecting basic and advanced built-in functions for data tasks. It is designed for data analysts, data engineers, machine learning and AI engineers, and related roles.

Hal yang diukur

Creating and manipulating NumPy arrays, and using its basic and advanced functions to solve everyday data tasks.

Creating arrays

Assess building NumPy arrays for use in numerical data tasks.

Manipulating arrays

Check reshaping arrays and selecting values from them.

Basic built-in functions

See how candidates choose basic built-in functions for a data task.

Advanced built-in functions

Check choices of advanced built-in functions in practical scenarios.

Question formats

Multiple choice

The candidate: Reads a short situation, table or statement and picks the right answer, or every right answer.

You see: Whether the candidate knows the material well enough to apply it, not just recognize it.

16 questions in 10 minutes, served one at a time.

Roles this test fits

Data analysts, data engineers, machine learning and AI engineers, data visualization developers, research software developers and other roles that work with numerical data in Python.

What the NumPy test can show

See practical code judgment
Questions ask what a few lines of Python produce or which expression solves a data task, giving you evidence beyond a resume.
Fair across setups
Questions avoid behavior that differs between operating systems or between recent NumPy releases, so no candidate is marked wrong because of their own setup.
Room to work out shapes
Candidates may use scratch paper, so they can trace an array's shape or values by hand when reasoning about a reshape or selection.

What you get for each candidate

Example report (fictional data)NumPy

74%Percentile 53. Benchmark: HireValid candidates, n = 1.413

Creating arrays86%

Manipulating arrays77%

Basic built-in functions60%

Advanced built-in functions71%

Integrity ScoreTingkat keyakinan tinggi

Stayed on the test tab throughout
No pasted answers
Answered at a steady pace

Scores, profiles and integrity signals are evidence for you to review alongside an interview, never an automatic decision.

Use this test free

Test integrity signals for review

Each candidate receives a different set of questions from large pools. Question order and answer options are shuffled, and the browser shows one question at a time; answer keys stay on HireValid’s servers. Candidates cannot go back to earlier questions. Timing runs on the server, so reloading restores the same question with only the remaining time. Question text cannot be copied or selected; a blocked copy attempt is recorded in the timeline. Personal invitation links expire, and a finished test cannot be taken again. HireValid records signals such as time away from the test tab, pastes into answers, and answers faster than a question can be read. These are summarized in an Integrity Score with an evidence timeline for you to review; the system does not decide on its own. With the candidate’s consent, you can add webcam photos at random moments.

Cara kami mencegah kecurangan dengan AI · Integrity signals

Use the score as one piece of evidence

Review the NumPy score alongside a short work sample and a structured interview. For a work sample, ask the candidate to create an array, reshape or select values, and explain a built-in function choice for a data task. Discuss how that work relates to the role; do not use the test score alone to make a hiring decision. For roles that also work with data frames or large-scale data, see Pandas and PySpark; for data pipelines, see ETL.

Pertanyaan wawancara terstruktur

How would you reshape an array to fit a particular analysis, and how would you check the result?
Listen for a clear explanation of the intended shape, the steps taken, and how they would confirm the result.
Tell me about a numerical data task where selecting specific array values mattered. How did you approach it?
Look for a relevant example, a reason for the selection approach, and awareness of the data being handled.
Suppose a short Python expression gives an unexpected result while working with measurements. How would you investigate it?
Listen for a step-by-step way to inspect the input array, the operation, and the output.

Understand scoring and benchmarks

Fairness and accommodations

Scenarios use neutral data such as sensor readings, measurements, test scores and stock counts, with metric units, no money and no local knowledge. Code follows common NumPy style with plain variable names, and questions avoid behavior that differs between operating systems or between recent NumPy releases, so no candidate is marked wrong because of their own setup. Text is kept short so the test measures NumPy skill rather than reading speed in English.

You can give any candidate extra time as an accommodation. Results are evidence for a person to review, never an automatic decision.

Provisional: reliability is reported once 200 candidates have completed it.

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Test details

A short, timed check of practical NumPy skill: building arrays, reshaping and selecting from them, and picking the right built-in function for a data task. Most questions show a few lines of Python or a brief work scenario and ask what the code produces or which expression does the job.

Questions are in English.
Aids allowed: Scratch paper.
Each question is answered once, in order, with no going back.
4 practice questions, 3 minutes, before the timed test.

NumPy, Python are trademarks of their owners. HireValid is not affiliated with or endorsed by them.

Pertanyaan yang sering diajukan

Will a candidate's NumPy version or operating system affect their answers?+

No. Questions avoid behavior that differs between operating systems or between recent NumPy releases, and code follows common NumPy style with plain variable names. A candidate is not marked wrong because their own setup behaves differently.

Who should take the NumPy test?+

It is intended for intermediate roles that work with numerical data in Python, including data analysts, data engineers, machine learning and AI engineers, data visualization developers, and research software developers. Use it when NumPy skills matter to the role.

What is the NumPy test like for candidates?+

The test has 16 multiple-choice questions and takes 10 minutes. Candidates may use scratch paper. The language is English, but the text is kept short and scenarios use neutral data such as sensor readings, measurements, test scores, and stock counts.

Can candidates try the NumPy test before taking it?+

Yes. The practice set has 4 questions and takes 3 minutes. It gives candidates a chance to experience the question format before the timed test. In the test itself, each question is answered once, in order, with no going back.