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Online Data Science & Analytics Test
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Test duration:
35
min
Notes
No. of questions:
12
Tie
Level of experience:
Entry-level/Mid/Senior

Data Science & Analytics Test

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%.

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About

Online Data Science & Analytics Test

DData 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 and 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.

Use iMocha's assessment to hire skill fit, remove bias, and save money!
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How it works

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
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
Topics Covered
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Data Visualization

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

Regression Analysis

The Data Science readiness Assessment checks knowledge of Regression analysis for estimating the relationships between a dependent variable and one or more independent variables.
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Machine Learning Techniques

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

The online Data Science online test gauges a candidate’s understanding of Exploratory Data Analysis, which refers to performing initial investigations on data to discover patterns, to spot anomalies, test hypotheses, and check assumptions with the help of summary statistics and graphical representations.
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Data Manipulation using R

The Data Scientist hiring test contains questions on steps to create small samples of data from a huge dataset. This is done as the entire data set cannot be analyzed at a time.
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Analytics with R & other tools

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

Question types :

Multiple Option

Topic:

Difficulty:

Hard


Q 1. You have been asked to train « Naive Bayes model for spam detection dataset

Using Python command, what wil you add in the given code at XXXX to deciore, it and train your modal for the given dataset?

import numpy os np

X= nporroyll 3. 2b[1 21 [2.21.[3,21)
Y= nporray(fi.a,a.1))

XXXX

from skinamnaive_bayas import

Gaussianna

otf = Gaussianne()

ceataie(x ¥)

from skinamnaive_bayas import

Gaussianna

otf = Gaussianne()

ceataie(x ¥)

from skinamnaive_bayas import

Gaussianna

otf = Gaussianne()

ceataie(x ¥)

from skinamnaive_bayas import

Gaussianna

otf = Gaussianne()

ceataie(x ¥)

Question types :

Multiple Option

Topic:

Machine teaming

Difficulty:

Hard


Q 1. Q2 Lets assume that you have 6 Pandas DataFrome(af) in the below tole.

Index Code Open High
0 AAPL 19877 70074
1 AAPL 19877 70074
2 AAPL 19877 70074
3 AAPL 19877 70074
4 AAPL 19877 70074

When the following commend is executed, what hoppens to the DatoFrome?

df= defiinat()
Y= nporray(fi.a,a.1))

Index Code Open High
0 AAPL 19877 70074
1 AAPL 19877 70074
2 AAPL 19877 70074
3 AAPL 19877 70074
4 AAPL 19877 70074
Index Code Open High
0 AAPL 19877 70074
1 AAPL 19877 70074
2 AAPL 19877 70074
3 AAPL 19877 70074
4 AAPL 19877 70074
it gives an error becouse of the third row which has on empty string.
None of these

Question types :

Multiple Option

Topic:

Data Transformation

Difficulty:

Easy

Question:

You have a Pandas DataFrame(df) in the following 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])


Options

  • <table border="0" cellpadding="0" cellspacing="0" width="229"> <tbody> <tr height="20"> <td height="20" width="37">&nbsp;</td> <td width="64">code&nbsp;</td> <td width="64">&nbsp;open&nbsp;</td> <td width="64">&nbsp;high</td> </tr> <tr height="20"> <td height="20">0</td> <td width="64">AAPL&nbsp;</td> <td width="64">&nbsp;198.77</td> <td width="64">&nbsp;200.74</td> </tr> <tr height="20"> <td height="20">1</td> <td width="64">ATVI&nbsp;</td> <td width="64">&nbsp;NaN&nbsp;</td> <td width="64">&nbsp;47.96</td> </tr> <tr height="20"> <td height="20">2</td> <td width="64">ADBE&nbsp;</td> <td width="64">&nbsp;269.47</td> <td width="64">&nbsp;272.16</td> </tr> <tr height="20"> <td height="20">3</td> <td width="64">&nbsp;</td> <td width="64">&nbsp;27.46</td> <td width="64">&nbsp;28.12</td> </tr> <tr height="20"> <td height="20">4</td> <td width="64">ALXN&nbsp;</td> <td width="64">&nbsp;138.02</td> <td width="64">&nbsp;NaN</td> </tr> </tbody></table>
  • <table border="0" cellpadding="0" cellspacing="0" width="229"> <tbody> <tr height="20"> <td height="20" width="37">&nbsp;</td> <td width="64">code&nbsp;</td> <td width="64">&nbsp;open&nbsp;</td> <td width="64">&nbsp;high</td> </tr> <tr height="20"> <td height="20">0</td> <td width="64">AAPL&nbsp;</td> <td width="64">&nbsp;198.77</td> <td width="64">&nbsp;200.74</td> </tr> <tr height="20"> <td height="20">1</td> <td width="64">ATVI&nbsp;</td> <td width="64">&nbsp;NaN</td> <td width="64">&nbsp;47.96</td> </tr> <tr height="20"> <td height="20">2</td> <td width="64">ADBE&nbsp;</td> <td width="64">&nbsp;269.47</td> <td width="64">&nbsp;272.16</td> </tr> <tr height="20"> <td height="20">4</td> <td width="64">ALXN&nbsp;</td> <td width="64">&nbsp;138.02</td> <td width="64">&nbsp;NaN</td> </tr> </tbody></table>
  • It generates an error because of the third row which has an empty string.
  • None of the options
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FAQ
What is Data Science?
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.NET Design Pattern test helps recruiters to evaluate candidates' ability to work on GOF Decorator Design Pattern to solve recurring design problems and design flexible and reusable object-oriented software

Why use iMocha’s online data science test?
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What are the key skills that recruiter should look for while hiring a Data Scientist?
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What are few interview questions that recruiter/hiring manager should ask while hiring a data scientist?
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How do you assess the data scientists?
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What is Data Science?
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Data Science is a combination of various tools, algorithms, and machine learning principles with the goal to discover hidden patterns from the raw data. This raw data is further analysed and used to make decisions and predictions making use of predictive causal analytics, prescriptive analytics, machine learning patterns for discovery, etc. These responsibilities of analysing the data is carried out by the Data Scientist who work with statisticians and mathematicians to crack the complex data problems.

How does data science analytics test help recruiters hire people?
Down Arrow Circle

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.

Why use iMocha’s online data science test?
Down Arrow Circle

iMochs's online data science test is used by top tech companies to vet data scientists and hire the best data scientists. iMocha's data science assessment will help you to:

  • Reduce time-to-hire by 40% with ready-to-use assessments
  • Minimize dependency on technical evaluation team by 50% with in depth skill-wise reports
  • Assess candidates faster with AI-LogicBox questions (an AI-based pseudo coding platform)
Can I combine the test with other tests?
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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 key skills that recruiter should look for while hiring a Data Scientist?
Down Arrow Circle

You can consider below technical as well as soft skills while hiring great data scientists-

Technical Skills:

  • 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 certifications preferred for this role?  
Down Arrow Circle

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 few interview questions that recruiter/hiring manager should ask while hiring a data scientist?
Down Arrow Circle

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 do clean up and organize big data sets?
  • What were the business outcomes or decisions for the projects you worked on?

What are the roles and responsibilities of data scientist?
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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

How do you assess the data scientists?
Down Arrow Circle

Assessing and hiring great data scientists is a challenging job. iMocha offers a ready-to-use online data science assessment which helps to quantify data science skills and select the most relevant candidate.

This assessment covers the most critical topics of data science like data science with Python programming, data science with R programming, Linear algebra, Machine learning algorithms, data mining, data wrangling and many more. The questions based on these topics are either MCQ’s or LogicBox. Our AI-LogicBox is an artificial intelligence based innovative pseudo coding platform for assessing skills for languages where online coding compilers are not available. Recruiters get comprehensive coding competency report with useful insights so that they can select relevant developers.

What are the required skillsets for this role?  
Down Arrow Circle

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?
Down Arrow Circle

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