Online Data Science & Analytics Test

Candidates Assessed

12754+

Organizations Served

132+

Our Online Data Science test is the preferred pre-employment test for recruiters and hiring managers to hire job-fit candidates for roles such as Data Scientist, Data Science Developer, Data Science Associate, Data Science Analyst, and Data Visualization Engineer. This Data Scientist test reduces hiring time by 45% and improves the interview-to-selection ratio by 62%.

About Online Data Science & Analytics Test

Data Science is an interdisciplinary field of processes and systems to extract knowledge or insights from data in various forms including data analysis fields such as statistics, machine learning, and predictive analysis. It is designed to check the analytical and data science methods. Data science includes methods and theories from different verticals like mathematics, information science, computer science & statistics.

Data Science online tests help recruiters and hiring managers assess the ability to extract, analyze and interpret data to provide a solution to businesses or support decision-making. Data science assessment requires applicants to solve questions on Data Visualization, Machine Learning Techniques, Analytics with R & other tools, Exploratory Data Analysis, Data Manipulation using R, and Regression Analysis.

Two important use cases for Data Science skill test
#1 Identifying job-fit candidates based on job roles
Our subject matter experts customize assessments on the basis of primary and secondary skills, like Data Management Gateway, Deployment, Rest API, and much more. Also, questions can be customized according to the requirement of job role. It will help recruiters measure a candidate’s capabilities in various areas for the job role.

#2 Skill-gap analysis of your employees
An individual’s skill level can be assessed with pre-and post-training assessments. These assessments show the growth of learners. Our skill platform is integrated with legacy LMS and Data Science assessments assist to perform skill gap analysis. Our Data Science assessments and questionnaire are easy to customize.

Are you a jobseeker looking to sharpen your skills?

Test Summary

Data Scientist Assessment helps you to screen the traits below:
- Excellent R data manipulation handling skills
- Analytics with R tools, python & machine learning techniques
- Understanding linear and non-linear regression models
- Strong knowledge of different statistical concepts
- Doing ad-hoc analysis and presenting results in a clear manner
- Ability to perform exploratory data analysis & regression analysis
- Data mining skills using state-of-the-art methods
- Experience with data visualization tools

Test Creation Process
Assessments are brilliant methods to assess candidates’ specific skills. All data science skills assessments are prepared by SMEs based on their industry experience. For example: Questions based on regression analysis, azure data factory are created by Data Scientist.

Test Customization
Data science test contains the latest and quality set of questions crafted by industry experts to cope with recent technological developments. You can also create a customized test according to your job role. For example, if you need to assess only data visualization skills of candidates, then send us an email, and our support team will deliver customized data visualization test within 3 days.

Test Analytics Report
iMocha’s powerful reporting & intelligent analytics will help you overview the candidate’s performance in each section of the data science tests at a glance. The candidate feedback module will ensure they have excellent experience with iMocha.

Test Duration: 35 minutes

No. of Questions: 12

Level of Expertise: Entry-level/Mid/Senior

Useful for hiring

Data Scientists
Data Science Engineer
Data Science Developer
Data Science Associate
Data Visualization Designer
Data Visualization Analyst
Data Analyst
Machine Learning Engineer

Data Visualization

The Data Scientist assessment test assesses candidates' skills to translate large data sets and metrics into charts, graphs, and other visuals.

Machine Learning Techniques

Our test evaluates knowledge of ML techniques and involves computers discovering how they can perform tasks without being explicitly programmed.

Analytics with R & other tools

The iMocha’s Data Science technical assessment assesses the ability to work on data analytics using the R programming language, an open-source language used for statistical computing or graphics.

Exploratory Data Analysis

The Data Science online test assesses a candidate's understanding of exploratory data analysis, which refers to performing preliminary investigations on data to discover patterns, identify anomalies, test hypothesis, and validate assumptions using summary statistics and graphical representations.

Data Manipulation using R

Data Scientist hiring test contains questions on steps to create small samples of data from a vast dataset. This is done as the entire data set cannot be analyzed together.

Regression Analysis

Data Science Regression Assessment checks knowledge of Regression Analysis to estimate the relationship between a dependent variable and one or more independent variables.

Sample Questions

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

Question types:

Multiple Option

Topic:

Machine Learning

Difficulty:

Hard

Q 1. You have been asked to train a Naïve Bayes model for the spam detection dataset.

Using the Python command, what will you add in the given code at XXXX to declare, fit, and train your model for the dataset?

import numpy as np

X = np.array([[-3, -2], [-1, -2], [2, 2], [3, 2]])
Y = np.array([1, 0, 0, 1 ])

XXXX

from sklearn.naive_bayes import GaussianNB
clf = GaussianNB()
clf.fit(X, Y)

from sklearn.naive_bayes import NB
clf = NB()
clf.fit(X, Y)

from numpy.naive_bayes import GaussianNB
clf = GaussianNB()
clf.fit(X, Y)

from pandas.naive_bayes import NB
clf = NB()
clf.fit(X, Y)

Question types:

Multiple Option

Topic:

Data Transformation

Difficulty:

Easy

Q 2. You have a Pandas DataFrame (df) in the below table.

Numeric text

When the following command is executed, what happens to the DataFrame?

df = df.fillna(‘’)
df = df.code.apply(lambda x: x[:-3])

	code	open	high
0	AAPL	198.77	200.74
1	ATVI	NaN	47.96
2	ADBE	269.47	272.16
3		27.46	28.12
4	ALXN	138.02	NaN

	code	open	high
0	AAPL	198.77	200.74
1	ATVI	NaN	47.96
2	ADBE	269.47	272.16
4	ALXN	138.02	NaN

It throws an error because of the third row, which has an empty string.

None of the options

Sample Report

View Full Report . . .

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Setting difficulty level of test

Choose easy, medium or hard questions from our skill libraries to assess candidates of different experience levels.

Combining multiple skills into one test

Add multiple skills in a single test to create an effective assessment. Assess multiple skills together.

Adding your own questions to the test

Add, edit or bulk upload your own coding questions, MCQ, whiteboarding questions & more.

Requesting a tailor-made test

Get a tailored assessment created with the help of our subject matter experts to ensure effective screening.

“When hiring Business Analysts, I had to assess the applicants on their logical reasoning & aptitude. However, assessing a large pool of candidates & acquiring unbiased results without any human hustle is difficult without an automated solution. With iMocha, I was able to filter more than 500 candidates within a short span of time.”

George Nichkov, Gett

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Frequently Asked Questions

How does data science analytics test help recruiters hire people?

It evaluates knowledge of the data visualization, machine learning techniques data manipulation using R and much more. It assesses candidates’ competencies on basic, intermediate, and advanced levels. Questions are available in MCQ, Multiple Answer Questions, fill in the blanks, descriptive, audio/video questions, AI-LogicBox, formats that make it easier for recruiters to assess candidates better.

Can I combine the test with other tests?

Yes, you can combine the Data science analytics with other tests. You are free to include related skills like Azure Data Factory, Big Data, Data Scientist with Python, and Data Analytics Excel test questions. These tests can be customized by adding multiple skills in a test to create an effective assessment.

What are the certifications preferred for this role?  

A recruiter should look for these certifications for data analyst:

Technical Skills:

Microsoft Certified: Azure AI Fundamentals
SAS Certified Advanced Analytics Professional using SAS 9
Open Certified Data Scientist (Open CDS)
Microsoft Certified: Azure Data Scientist Associate
SAS Certified AI and Machine Learning Professional
Tensorflow Developer Certificate
SAS Certified Data Scientist

What are the roles and responsibilities of data scientist?

The roles and responsibilities completely depend on an organization’s needs. A data scientist's job is to collect data in bulk, analyze them and then to extract essential information for business growth. Later, that data can be used to increase the efficiency of the businesses make data-driven decisions.

Some of the roles and responsibilities of Data scientist are:

Data collection and identification of data sources
Analysis of structured and unstructured amount of data
Create solutions as well as strategies for business problems
Develop data strategy with leaders and team members
Data presentation using different data visualization tools and techniques

What are the required skillsets for this role?  

You can consider these technical as well as soft skills while hiring great data scientists:

Fundamentals of Data Science
Statistics
Programming knowledge
Data Manipulation and Analysis
Data Visualization
Machine Learning
Deep Learning
Big Data

Soft Skills:  

Communication Skills
Storytelling Skills
Structured Thinking
Curiosity

What are the most common data science assessment interview questions?

Here are few important questions that you can ask to data scientists & predict their technical proficiency:

Which technique will you use to predict categorical responses?
Can you use machine learning for time series analysis?
Explain what precision and recall are. How do they relate to the ROC curve?
What are the similarities and differences between R and Python?
How is logistic regression done?
Do you know how to make an R decision tree?
How do you build a random forest model?
What are your favorite data visualization tools?
How to clean up and organize big data sets?
What were the business outcomes or decisions for the projects you worked on?

What is the package of data scientist?

According to sources, Data Scientist can make somewhere between $96k to $135k per year. The amount excludes stock options, bonuses, RSUs, and profit-sharing.