Online R Test for assessing candidates' proficiency in R for data science roles

R is an open-source statistical programming language that data scientists and analysts across the globe use to interpret data. Its ability to interpret the data graphically helps produce easily understandable, high-quality data visualizations. From the statistical and graphical analysis of data to data manipulation, R includes a wide range of features that make it immensely popular among data scientists and business leaders in diverse fields.

R Test is the ideal pre-employment skills assessment given to potential candidates to identify the best-fit talent in a large talent pool. The test is designed to optimize hiring by reducing screening time and hiring costs. It enables tech acquisition experts and hiring managers to gain a holistic overview of a prospect's on-the-job performance and role suitability through various technical questions.

With this R Skills Assessment, employers can see where candidates stand in terms of their in-depth knowledge, skills, and experience in using R programming language to perform data analysis, visualization, etc. This 60-minute test includes 18 multiple-choice questions (MCQs) and two coding assessments to be solved in real-time on an R simulator. The test is intended to assess applicants' knowledge and skills in R programming, R libraries, and their hands-on programming abilities. 

Key profiles this test is helpful for:

• Data scientist  
• Data engineer  
• Machine learning engineer  
• Statistician  
• Data analyst  
• Business analyst  

Overview

An increasing number of organizations across industries have realized that business success, to a significant extent, is characterized by a firm's ability to gather, store, analyze, and produce data faster than its competition. Consequently, this big data revolution has increased the demand for data scientists/engineers with R programming, Hadoop, Python, and other related skills. With machine learning and big data analytics guiding intelligence in nearly all internet-linked devices, smartphones, and applications, R is a powerful yet versatile statistical tool that enables data analysts to make sense of large troves of data. In addition, they can use R programming to perform statistical data analysis quickly and more efficiently compared to other statistical analysis tools.

By 2027, the global big data market is expected to grow to US$103 billion (about US$320 per person in the US). This projection underscores the underlying need for data scientists who can explore, analyze, model, and visualize data for businesses that base their operations on it. Therefore, excellent data science skills are essential for anyone envisioning a flourishing career. Furthermore, many data engineers, scientists, machine learning engineers, etc., prefer R over other languages owing to its usefulness and adaptability in data-related tasks. Interestingly, tech professionals can utilize several packages and libraries that enhance R’s functionality and simplify the task of data professionals. Unsurprisingly, R professionals are well-paid in different industries and are highly sought-after.

While hiring dedicated data professionals, talent acquisition specialists can use an R Test to assess a candidate's domain knowledge and identify the best person for the role. This pre-hiring test provides recruiters with an objective understanding of how well-aligned a candidate is to the position in terms of skills, knowledge, and competencies. In addition, this R Assessment can significantly reduce technical screening time, helping employers find job-ready candidates and reduce unnecessary hassles in large-scale recruitment drives.

Hiring managers leave no stone unturned to recruit the best talent for a given opening. However, when dealing with many applicants, all of whom proclaim their expertise in R for data science, it can take time to identify which applicants have the skills and knowledge aligned with the given role's requirements. The R Test provides a comprehensive way of evaluating the test-takers' skill level. Candidates who perform well on the assignment will advance to the next stage; those who do not will be screened out. Thus, the test assists recruiters in shortlisting those candidates to the latter stages who have expertise in using R at the skill level required for the role.