What is the package of a data scientist?

A data scientist package varies depending on the company's role, location, and requirements. However, the average pay of a data scientist in the US is $124,693 per year.

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Data Science & Analytics Test

Test duration:

35

min

No. of questions:

12

Level of experience:

Entry-level/Mid/Senior

Data Science & Analytics Test

Q: What is Data Science?

Data Science is the method of identifying hidden patterns from raw data. In order to do so, data scientists utilize a set of numerous tools, machine learning principles, and algorithms on structured and unstructured data. They also crack complex data problems to make insightful business decisions and predictions.

Q: How does data science analytics test help recruiters hire people?

The data used by data scientists are usually a collection of data gathered from various resources and compiled in a structured format to make an insightful decision. Hence, data science analytics is the collection of candidate data arranged logically to help recruiters with predictive power and more accurate insight into candidates' skills.

Q: Can I combine the test with other tests?

Yes, iMocha enables you to custom-create your assessments according to the requirements of your organization. For example, you can personalize your Data science analytics test by combining it with other related technical and non-technical skills. For example, you can combine Azure Data Factory, Big Data, Data Scientist with Python, Data Analytics Excel, communication test questions, etc.

Q: What are the certifications preferred for this role?

Some of the common certifications preferred for Data Science analytics roles are: • 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

Q: What are the most common data science assessment interview questions?

Here are a few important questions that you can ask data scientists: • 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?

Q: What are the roles and responsibilities of data scientists?

Some of the common roles and responsibilities of a Data scientist are: • Analysis of the structured and unstructured amounts of data • Creation of strategies and solutions for business problems • Data strategy development with leaders and team members • Data presentation using different data visualization tools and techniques • Using valuable data sources to mine them for useful information • Using tools for machine learning to choose features, build, and improve classifiers • Preprocessing both structured and unstructured data, as well as improving data gathering processes to incorporate all pertinent data needed to create analytical systems • Preparing, extracting, and verifying data integrity for analysis • Finding patterns and solutions through the analysis of a lot of data

Q: What are the required skillsets for this role?

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

Our Data Science test enables recruiters and hiring managers to gauge candidates' knowledge of Data Scientists, Data Science developers, Data Science associates, Data Science analysts, and Data Visualization engineers. This Data Scientist test helps you reduce your hiring time by 45% and improves the interview-to-selection ratio by 62%.

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Data science assessment 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 analytical and data science methods. It 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. Using this assessment, recruiters can assess candidates' skills such as 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 the job role. With the help of this feature, recruiters can measure a candidate's capabilities in various areas for the job role.

‍#2 Skill-gap analysis of your employees

This feature enables recruiters to assess the individual skill level of your employees. Utilizing the pre and post-training assessment helps you determine your data science experts' existing and gained knowledge. Data science skills assessment test also help to check your organization's overall skills level.

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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

In order to help you assess the technical and non-technical skills of data science skills of candidates, we offer various data science tests. All data science skills assessments are prepared by SMEs based on their industry experience. For example, only Data Science experts create questions based on regression analysis, azure data factory, and more.

Useful for hiring

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

Test Duration

35

min

No. of Questions

12

Level of Expertise

Entry-level/Mid/Senior

Topics Covered

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.

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.

Exploratory Data Analysis

The Data Science online assessment 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.

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.

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 type

Multiple Option