Career Opportunities in R Programming Language [Ultimate Guide]


R is a programming language that is becoming very popular in the data analytics and data science field. There is no denying that there are umpteenth number of opportunities in data science for you to explore if you possess the right skill set. With good command of the R language, you can take various job roles such as data analyst, statistician, and data scientist. As of today, these are the highly paid job roles in the market. A Career in R is an excellent choice even for those who are already in the data science domain and looking to upgrade their career to the next level.

If you still have doubts about whether learning an R programming language is worth it or not. In that case, this article will help you in taking all your worries away, explain how R language has been a game-changer in the industry and will give you deep insight into the need to learn and look for career options in R.

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Why is the R Language so Popular?

We all live in a world that is driven by data and technology. Almost 2.5 quintillion bytes of data get generated every day. Companies utilize this large pool of data to create a powerful impact on their business growth. Hence, they are always on the lookout to find people who have the relevant skills to analyze this raw and unstructured data and provide meaningful insights.

It is not always easy to work with these complex data sets without knowing statistical computing. Hence, a tool is required that can help you in statistical visualization. R has the salient features of statistical computing and is an excellent choice for such data visualization tools as it makes it easier to analyze large complex data sets. If you want to get a stronghold in the data science world, you must learn and make a career in R.  

Another reason why R is a popular language tool is that it is an open-source tool. It is instrumental in analyzing heavy data, thus making it suitable for statistical analysis or calculations.

R provides the vast library used for visualization, giving it a competitive advantage over other programming languages. 

Its vast usage and applicability are another reason behind its popularity. The use of R is seen in almost every industry. It is used in portfolio management, risk management, banking industries, etc. 

The language R sees wide adaptability due to various other reasons as well, such as having cross-platform feature that allows it to run on various platforms. There are different R programming jobs in the market, and the job aspirants can apply for these jobs in numerous industries and gain better chances of accelerating their careers.

Following are the reasons that will explain why you should learn and make a career in R:

  • According to IEEE Spectrum’s survey, R ranks seventh among the top ten programming languages of 2018.
  • It is the most sought and popular programming language that is used mainly in the data science and analytics industry, making career options in R innumerable.
  • R is a free, open-source language that can be easily downloaded from the internet and run on several operating systems such as Windows, Linux, Macintosh, etc.
  • R has a very vast and big community. You may have seen many seminars and boot camps being organized across the world that facilitate R education.
  • R allows to running various machine learning algorithms.
  • Supporting data wrangling is another advantage of using R.
  • The language is constantly evolving and adapting, thus making it relevant and valuable.

Read: R Tutorial For Beginners

How is R Programming Language a Game Changer in Data Science?

R is a free, open-source language that is contributed by many people around the world through forums, seminars, social media, conferences, and boot camps. The community is expanding continuously, and many people are contributing to R development. This has made R secure a place in the list of top ten programming languages. Due to its cross-platform compatibility, package diversity, and outstanding graphical output features, it has become the first choice for the data science and analytics industry.

Here is a list of reasons that makes R the game-changer:

  1. The open-source nature of the R language provides a boost to companies that are looking to innovate. R includes all the functions that are required for data science applications such as visualization, modelling, forecasting, etc.

The open- source feature of R is attractive and beneficial to the organization as there is no requirement for any fees or licenses for it to run.  This helps in venturing out to the new territories, as the code can be redistributed or changed according to the users’ requirements.

2. Earlier, R was used extensively in academia for research purposes as it offers several tools for analysis. With the continuous increase in data analysis demand, R has become the priority for developers in commercial sectors as well.

R helps in performing complex statistical analysis as well, thus making it useful for performing complex calculations. It provides for important features like clustering, analytical models, etc. R eases out the task of data scientists in providing relevant insights and customizing data collection.

3. R has various inbuilt libraries and packages that make data wrangling an easy task. Hence, it is given preference in the data science community.

Data wrangling helps make the data compatible with the end system, thus enhancing its readability and usability. It has become a very useful feature in R data science jobs. The data scientists can automate the flow of data within the system using data wrangling.

4. With strong demand and intense competition in the market, companies who previously depended on legacy platforms for computational and statistical analysis are now making a shift to R. By far, R has been adopted by more than 2 million professionals across the world.

What Education to Choose to Start a Career in R Language?

You do not have to go through any special education to learn R. However, if you understand programming language well, it becomes easier and faster to learn R as you will grasp logic fast. It is also a good idea to start coding with real-world problems so that you can relate to them. The following three skills will help you catch things faster:

· Statistical and Mathematical Knowledge

· Understanding of different types of graphs that are used for data representation

· Basic understanding of any programming language

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Big Companies that Are Using R

Here is a list of a few big companies that are using an R programming language for their data analysis and creating great opportunities for a career in R.

· Google: Google is using R to calculate returns on advertising campaigns and to enhance online advertising efficiency.

  • Facebook: Facebook is using R for updating the status and social network graph.
  • Microsoft: Microsoft is also using R for its Azure machine learning framework.
  • Twitter: Twitter is using R for statistical data modelling.
  • John Deere: John Deere is using R for geospatial analysis.
  • Ford Motors: Ford Motors is using R for statistical analysis.
  • Mozilla: Mozilla is using R to visualize the web activity of the Firefox web browser.
  • Amazon/ Flipkart: They are using R for statistical analysis.
  • Infosys: It uses R for exploratory data analysis and machine learning.
  • HCL: It uses R for machine learning.
  • Twitter: It uses R for data visualisation.

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What Are the Job Prospects of R Programming Language?

In this technology and data-driven world, data analysts are changing the face of business intelligence. The huge quantity of data availability has made data analysis or science professionals crucial to product development. As a result, the hiring of data science professionals has increased at a massive rate.

R programming language is the primary choice for professionals who are engaged in data analysis as it offers several benefits. There are endless opportunities for both novice and expert R professionals to explore. Some big and famous companies like Facebook, Google, Twitter, etc. have adopted the R language to fulfil their analytical business goals.

Hence, it is evident that the R programming language can land you an opportunity in one of the most popular companies in India and overseas. If you are curious to know about R professionals’ salaries in India and subsequently why a career in R is a great option, do read the article R Developer Salary in India: For Freshers & Experienced.

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What are the Job Roles in R?

Knowledge in R not only helps you secure a job in the IT industry but also opens the door to several other opportunities where data is used at a large scale to create analytics-based solutions such as healthcare, banks, education, the financial sector, government departments, etc. R professionals are in high demand all over the world. Here is the list of positions that are available for R professionals, proving the multifaceted career options in R.

Data Scientist

Data scientists are the professionals who extract data from multiple sources, clean it, transform it into a structured and readable format, analyze it, and derive meaningful and useful insights from it. In today’s competitive world, it is the most demanding job role for R professionals. Due to a lack of knowledge and the right expertise, many data scientist positions remain vacant every year. 

A data scientist is given the responsibility to manage various important tasks. They are required to identify the data, and gather structured or unstructured data in order to apply the algorithms pertaining to the topic of research. They build predictive models and convey the results to the stakeholders, thus making the organization data centric and assist in decision making based on accuracy rather vague perceptions. 

They are required to be having certain skill sets that help them in performing their tasks. The data scientist must be proficient in mathematics and statistics, have good knowledge of programming languages, data visualization, project management, technical expertise and knowledge of tools, good communication, etc. There are many R data scientist jobs and one has to have solid skill sets required in the industry and an ethical approach to their work to be successful.

It is considered as one of the high paying careers. On average, a data scientist procures the compensation of 10.5 lakhs per annum. The salary ranges from 4.5 lakhs per annum to 25.8 lakhs per annum (Source). The salary bracket may be higher owing to various factors.

Data Analyst

A data analyst is one who has a good understanding of handling complex data sets and possesses good technical and analytical knowledge. Data analysts are responsible for extracting and mining datasets to provide insights that help the company in making business decisions. R statistical libraries help big time in achieving such results. Hence, there will be a boom in demand for R professionals.

The data analysts’ market size is expected to grow; the market is expected to reach USD 655.53 billion by 2029 (Source).

The data analysts are an asset to any organization. Along with bringing technical expertise, and they also ensure the quality and accuracy of data. They acquire the data from primary and secondary research sources. They make sure to identify, analyse and interpret the trends from the data sets.

Some of the skills required from a data analyst include SQL, Statistics, Programming languages, tools understanding, knowledge of R, Python, Matlab, Data visualization, Machine learning, Linear algebra algorithms, etc.

On average, the salary procured by a data analyst is 4.3 lakhs per annum. The average salary ranges from 1.9 lakhs per annum to 11.5 lakhs per annum (Source).

Business Analyst

A business analyst is one who creates technical solutions for various business problems. Their job role demands developing solutions to advance the efforts of the company and fulfil the business requirements. Due to R’s extensive package, R provides various tools that are used for business intelligence solutions.

Business analysts are required to analyse the data and provide solutions to the stakeholders that help in business growth. They are given the opportunity to identify, analyse and develop processes that help in achieving the business objectives. 

The business analysts must be well versed in analytical skills, problem-solving, documentation, testing, business acumen, communication, collaboration, interpersonal, etc.

The average salary of a business analyst is 7.0 lakhs per annum. The average salary ranges from 3.0 lakhs per annum to 15.0 lakhs per annum (Source).

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Quantitative Analyst

A quantitative analyst is one who is positioned in finance, telecom, and banking organizations. Since R is used extensively for statistical computation, which makes it ideal to use for quantitative analysis.

Quantitative analysts are responsible for developing complex models for organisations to help them in making financial, risk management and business decisions. They are also responsible for reviewing and updating models. They develop and devise methods that help in assessing the performance of credits, operations, etc. There are various R  jobs available in reputed companies as well.

Some of the skills required from quantities analysts are mathematical, financial, programming skills, numerical skills, data analysis, etc.

The quantitative analysts are paid good compensation and are in demand. On average, the quantitative analysts procure a salary of 12.0 lakhs per annum. The average salary ranges from 3.0 lakhs per annum to 32.0 lakhs per annum (Source). The salary brackets could be higher to various factors such as experience, skill sets, location, company, etc. The demand for R language is very high and is reflected in the R  language salary.

Data Visualization Analyst

R’s provides a ggplot2 package which is most famous for data visualization. R has some other packages (for example, plotly) as well that provide visually appealing graphs and plots to their users.

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In this article, we went through the importance of R in the data science world and gave insights about how learning R language can help you get a job in one of the big firms with a huge salary and excellent benefits. In the end, we conclude that R is an excellent platform for professionals who are engaged in statistical data analysis.

With the advancement in the data science and analysis field, the popularity of making a career in R is going to increase. Companies are opening a lot of new positions for professionals who have a good understanding of R language and are also encouraging their staff to get engaged in the training program, online, or classroom courses to build their expertise in the R language.

The shortage of people with the right expertise is a sign that you should start learning R at the earliest to kick start your bright career in the data science or machine language field.

What jobs can I obtain with the R programming language?

If you are proficient with the R programming language, you can expect plenty of job opportunities in the big data and business analytics profession. This programming language is in huge demand because of the rise in the importance of data in every industry. There is a huge scope for entry-level as well as experienced R language programmers in the market. Every job related to data is found to be a good fit for professionals who possess sound knowledge of the R programming language.

Some of the top job positions for R language programmers are:

1. Data Scientist
2. Data Architect
3. Geo Statisticians
4. R programmer
5. Quantitative Analysis with R
6. Data Visualization Analyst
7.Data Analyst

There is a huge demand for R programmers in the market, and you can expect to get a decent job with a high salary in different fields.

What is the scope of R programming in the market?

R language has turned out to be the most effective tool for data science and statistical analysis because of its extreme versatility and open-source nature. There is a huge shortage of data science professionals in the market. This is why it is considered to be a perfect time for both beginners and expert R programmers to step into this field.

As per different job portals like Indeed, Monster, LinkedIn, and Glassdoor, there are thousands of job postings for R programmers and data scientists in the market. R programmers can expect a very bright future and excellent scope in different job roles like data scientists, data analysts, R programmers, business analysts, data visualization experts, and many more.

Should I be using Python or R?

Python is considered to be a better option for large-scale applications and machine learning functionalities, along with its use in data analysis within web applications. On the other hand, the R programming language is considered to be an effective one for statistical learning, with unmatched libraries available for data experimentation and exploration.

Using any programming language from Python or R will completely depend upon your programming knowledge as well as the requirements. Another major difference is that Python is pretty easy for beginners to start with, while R programming is a bit difficult to understand and get acquainted with.

Who uses R most?

The language R is widely used by statisticians, data scientists, data analysts, business analysts, quantitative analysts, etc.

Do companies still use R?

R language is constantly evolving and serves as one of the best tools for solving complex calculations. The demand for this statistical software is exponentially increasing. It serves as one of the standard tools for various companies.

Is R in high demand?

Yes, R is in high demand. There are various companies that use R due to its benefits. The demand for the language is also reflected in the high compensation drawn by the professionals.

What is the scope of R?

R is used for statistical analysis and better computing abilities. The language is sued for cleaning, analyzing, and visually representing the data. The scope of R is in almost every industry such as e-commerce, retails, entertainment, finance, etc.

Is R used at Google?

Yes, the language R is used in Google. The language is used to calculate the ROI on the campaigns and advertisements. The company uses R to perform large scale data analysis.

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