Data Science Aptitude Test

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.

‍

Start your free trial

Data Science Aptitude Test

Data Science is an interdisciplinary field that incorporates data analysis fields including statistics, machine learning, and predictive analysis. Its purpose is to evaluate analytics and data science techniques. Methods and theories from other sectors, such as mathematics, information science, computer science, and statistics, are also used in data science.

Data science aptitude test is designed and validated by experienced Subject Matter Experts (SMEs) to assess and hire data science professionals as per industry standards. Check out the list of data science interview questions and answers to ask for Technical Recruiters & Hiring Managers.

Wondering what other skills we have in our World’s Largest Skills Assessment library?

Visit here

How it works

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.

Useful for hiring

Data Science Expert
Data Science Engineer
Data Science Consultant

‍

Test Duration

min

No. of Questions

Level of Expertise

Entry Level/Mid/Expert

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.