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Data Analyst (Using R) hiring test- Assess R skills & data analysis expertise

The Data Analysis (Using R) Hiring Test is an online technical assessment for hiring managers and recruiters to evaluate candidates' expertise in the R programming language and data analysis capabilities. This comprehensive evaluation identifies developers capable of handling complex data challenges, ensuring informed hiring decisions for roles such as business analysts, data scientists, data analysts, data visualization creators, etc. 

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Inside this Data Analyst (using R) Assessment

The Data Analyst (Using R) Hiring Test is a pre-employment assessment designed to enable recruiters and hiring managers to assess candidates' R proficiency and data analysis skills. Developed and validated by subject matter experts (SMEs), this online evaluation includes questions related to database query writing, hands-on programming, SQL server basics, R programming, and R libraries.

The database query writing section houses questions related to MS SQL, where candidates are assessed on their ability to develop optimized and precise database queries. In the hands-on programming section, candidates will be presented with practical R programming scenarios using the R simulator. This ensures that assessment takers have practical knowledge and application of R basics, which are required for data analysis tasks. 

In addition, the assessment comprises questions to assess test-takers' understanding of SQL Server fundamentals and their familiarity with R libraries like GGPLOT2 and DPLYR for data visualization and manipulation. 

By administering the Data Analyst (using R) Hiring Test, one can make informed decisions and identify the best talent capable of executing data analysis tasks efficiently. Thus, the test ensures the right fit for roles that require proficiency in R programming and data analysis. 

The following roles can be primarily evaluated using this Data Analyst Test:

  • Big data analyst (using R programming) 
  • Database analyst 
  • Business analyst 
  • Data visualization creators


Skilled data analysts proficient in R programming are among the most in-demand professionals globally. Nowadays, the pressing priority for hiring the best data analysts is observed in many companies and industries. Any business that excessively relies on data needs skilled analysts to analyze it. A data analyst generates insights using data so stakeholders can make business decisions and reach meaningful conclusions based on those insights. The analyst's role and KRA will vary slightly across industries, organizations, and departments. 

Even for aspiring data analysts or researchers, the knowledge from importing and cleaning data to manipulating and visualizing it in R is necessary. R skills are invaluable for analysts in addition to understanding popular R packages like - GGPLOT2, DPLYR, etc. As they work with various crucial datasets, data analysts are known for their statistical skills for hypothesis testing, data manipulation, and exploratory data analysis (EDA) skills.  

With data becoming the most important currency for businesses to operate at their maximum potential, hiring top data analyst talent has become the foremost concern for employers.

In addition, hiring candidates for data analyst roles has become arduous because finding high-quality talent in a highly competitive job market is more challenging than it seems. Moreover, talent assessment is significantly difficult because the one-size-fits-all approach does not work here, and every organization's talent needs are specific to its business objectives.

An efficient way to determine if a candidate is a good fit for the role is to assess an applicant's employability skills using the Data Analyst Hiring Test in the hiring process. Hiring managers will understand how much the candidate's on-the-job skills and work readiness match the organization's requirements with this online screening method. 

As candidates undergo the vetting and screening through the Data Analysis Assessment, employers can rest assured that the selected candidates are up to the required standard in terms of skills, competencies, and experience. Moreover, the assessment result reports thoroughly capture every aspect of an examinee's performance and give in-depth insights into their potential fit. 


This Data Analyst Skills Test is a part of following Skills Libraries

The data analyst skill assessment gauges expertise in performing data analysis and statistical operations in the R language. This online assessment is created by a team of SMEs and is ideal for assessing beginner to moderately experienced data analysts.

Data Analyst (using R) Hiring Assessment Competency Framework

Get a detailed look inside the test

Data Analyst Competencies Under Scanner

Data Analyst (using R)


Hands-on programming:

This assessment evaluates a candidate's ability to efficiently write codes in the R programming language, ensuring they can handle data analysis tasks effectively.

R programming:

This section evaluates test takers' applied skills in R - functions, providing insights into their proficiency in using R for various data manipulation and analysis tasks.

Database query writing:

This section includes questions related to MS SQL, where candidates are evaluated on their ability to create precise and efficient database queries in MS SQL. Strong query writing skills are crucial for accurately retrieving and manipulating data.

R libraries:

This section helps determine assessment takers' applied skills in R - DPLYR and R - GGPLOT2. This evaluation helps determine their aptitude in utilizing R libraries for data manipulation and visualization tasks.

SQL server basics:

This section evaluates respondents' SQL server skills, aiming to understand their knowledge of SQL server fundamentals, a crucial aspect of data analysis. By subjecting candidates to a thorough assessment of these competencies, hiring managers can identify proficient data analysts who can tackle complex data challenges and make data-driven decisions efficiently.

Customize This Data Analyst Skills Test

Flexible customization options to suit your needs

Set difficulty level of test

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

Combine multiple skills into one test

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

Request a tailor-made test

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

The Mercer | Mettl Data Analyst Assessment Test Advantage

The Mercer | Mettl Edge

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  • State of the art examination platform
  • Inbuilt Cutting Edge AI-Driven Proctoring
  • Simulators designed by developers
  • Tests Tailored to Your business needs
  • Support for 20+ Languages in 80+ Countries Globally

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Frequently Asked Questions (FAQs)

You can follow these simple steps to hire data analysts: 

 1) Write a well-thought-out job description 

 A well-explained job description can strike a responsive chord with data analyst aspirants. A thorough data analyst JD includes a well-written summary of the role, responsibilities, and required skills. In addition, you can have keywords that job seekers use to search for these jobs, such as: 

  • Business analyst 
  • Financial analyst 
  • Data analyst 


 2) Pre-employment testing to assess data analysis skills and filter out ineligible candidates 

A Data Analysis Test is a technical assessment prepared by subject matter experts to understand and assess a candidate's expertise in analyzing high-level quantitative data. The test outcome reveals how well the candidate will perform in the actual job.

 3) Interviewing candidates for data analyst positions 

 Potential candidates for these positions will be optimistic in answering data analyst interview questions regarding: 

  • Advanced SQL and Excel 
  • ETL processes 
  • Statistics 
  • Project management 
  • Interpersonal skills 

Listed below are some must-have skills for data analysts: 

  • R or Python-statistical programming 
  • Data visualization 
  • Critical thinking 
  • SQL 
  • Machine learning 
  • Microsoft Excel 
  • Presentation skills 

The demand for data analysts is at an all-time high, as stated by the World Economic Forum, highlighting that data analytics is among the top ten careers in 2020 and beyond. 

Data analysts do not need to have exceptional coding skills but must be well-versed in data visualization software, analytics software, and data management processes. Data analysts should also have effective communication skills because they must work with teams with different levels of technical knowledge. 

Mercer | Mettl's Data Analyst (Using R) Hiring Test evaluates the candidates’ abilities to extract information by analyzing data and suggesting outcomes and their proficiency in using R. It is used for pre-employment screening. However, data analysts who use R for their daily work should know how to leverage the functionality given by R packages to unveil powerful insights from data. 

The answer to this question varies based on the type of company and the level to which an enterprise has adopted data-driven decision-making practices. However, the responsibilities of an analyst usually include the following:

  • Designing and maintaining databases and data systems; this includes tasks such as solving various data-related issues and coding errors. 
  • Data mining from primary and secondary sources and compiling that data in a human and machine-readable format 
  • Employing statistical tools to explain data sets, putting particular emphasis on trends and patterns that offer opportunities for implementing diagnostic and predictive analytics 
  • Exhibiting the relevance of their responsibilities concerning global, national, and local trends that influence both their company and industry 
  • Creating reports for senior leaders to effectively communicate trends, predictions, and patterns based on relevant data. 
  • Teaming up with engineers, programmers, and executive leaders to find and discuss avenues for process modifications, system improvements, and data governance policies 
  • Providing adequate documentation that enables stakeholders to comprehend the steps of the analysis process