Data Science Aptitude Test

Candidates Assessed

15645+

Organizations Served

143+

Data science aptitude test helps recruiters evaluate candidates required technical as well as aptitude skills. This assessment is a good combination of questions on data science, SQL, data wrangling and quantitative aptitude to quantify candidates' aptitude for data science.

Test Summary

Data science aptitude test helps to screen candidates possessing the following traits:

Good knowledge of Classification and Regression Algorithms
Relevant experience in Data Extraction and Mining
Strong knowledge of vImbalanced Datasets & Sampling Distributions

Good experience in Optimizing Functions and Information Theory
Hands-on experience & knowledge in Data Wrangling and Correction
In-depth understanding of Numerical Ability

This test is designed considering EEOC guidelines. It will help you assess & hire diverse talent without any bias. Recruiters/hiring managers can access comprehensive reports for each candidate that will give an overview of candidate’s performance in each section at a glance. Moreover, Test Insights section helps to identify job fit candidates more accurately with score distribution and section analysis features.

This test may contain MCQ's (Multiple Choice Questions), MAQ's (Multiple Answer Questions), Fill in the Blanks, Descriptive, Whiteboard Questions, Audio / Video Questions, AI-LogicBox (AI-based Pseudo-Coding Platform), Coding Simulations, True or False Questions, etc.

Test Duration: 60 minutes

No. of Questions: 23

Level of Expertise: Entry Level/Mid/Expert

Useful for hiring

Data Science Expert
Data Science Engineer
Data Science Consultant

Topics Covered

Classification and Regression Algorithms

This test helps recruiters to understand the candidate’s knowledge of dividing the dataset into different classes and ability to find the best fit line, which can predict the output more accurately.

Data Extraction and Mining

This test helps recruiters in evaluating the skills of a candidate to analyze large data sets using machine learning, statistical and mathematical techniques and extraction of data from online sources into centralized storage.

Imbalanced Datasets & Sampling Distributions

This test aids the recruiters in analyzing candidate’s understanding of classification data set with skewed class proportion and statistics through repeated sampling.

Optimizing Functions and Information Theory

This test helps recruiters in quantifying a candidate's ability of maximizing or minimizing a real function by choosing input values from an allowed set and computing the value of the function in data science.

Data Wrangling and Correction

This test helps recruiters understand a candidate’s skill of uniting complex data sets for easy analysis and checking whether data is correct or inaccurate.

Numerical Ability-Quantitative Aptitude

This test aids the recruiters in understanding candidates speed of the executing tasks related to handling of numbers.

Sample Questions

Choose from our 100,000+ question library or add your own questions to make powerful custom tests

Question types:

Multiple Option

Topic:

ACF, PACF

Difficulty:

Hard

Q 1. Which of the following ACF plots represents a stationary time series?

graph images

Both Plot 1 and Plot 2

Only Plot 1

Neither Plot 1 nor Plot 2

Only Plot 2

Question types:

Multiple Option

Topic:

Data Extraction and Mining - Genetic Algorithms

Difficulty:

Hard

Q 2. Suppose a genetic algorithm uses chromosomes of the form x = abcdefgh with a fixed length of eight genes. Each gene can be any digit between 0 and 9. Let the fitness of individual x be calculated as: