Salary Trend of R users

Why R programming still rule the data science field?

R is ruling the data science field. It is the most popular and powerful language used currently by data scientists, as per the survey conducted by O'Reilly Media in 2014. Below are the reasons R still rules the data science field.

Open Source

R is an open-source language that is free to use for anyone across the globe. It can run on all the operating systems out there. R provides numerous free libraries like Hadoop's project library, which helps users manage their data in their Hadoop environment.  

All in one package

R provides almost all the standard data analysis tools for the analysis of various kinds of data. It enables users to perform different kinds of operations on data in order to analyze it better. It provides various tools for models like ANOVA, Regression, Tree Models, etc., in order to do the task fast and easily.

Excellent charting benefits

R provides various powerful tools to create graphs and charts for data visualisation. Various kinds of charts, like bar charts, lattice charts, pie charts, etc., can be created effectively using R. Various blogs like FlowingData, The New York Times, The Economist, etc., use R-based graphics.

Robust online community

R provides the most quick and consistent online support to its users. It has very interactive discussion forums for its users. The user will get answers to their queries rapidly and accurately.

Powerful package ecosystem

R has a powerful package ecosystem for statisticians. It supports advanced packages like ggplot2 and dplyr, which are used for plotting and data manipulation. The carpet package in R helps to implement various machine learning algorithms through a unified interface.

From the above points, we can clearly understand why R still rules the data science field.

What are the market trends of R programming?

R language has been kicking around since 1997. It is proving to be an effective choice compared to other costly statistical tools like SAS or Matlab. There is no doubt over the fact that R is one of the most popular languages. Below are some of the details of the industries that hire R programmers:

• Professionals with R skills in healthcare can earn a lot of money, and it is expected to increase as demand for R skills grows. Further, according to payscale, the average salary for a Health Care Analyst with R skills is $82329. Similarly, the average salary for a healthcare analyst is around ₹4,25,000 in India.
   
• Similarly, technical consultants are making a lot of profit in this industry. The average salary for a Technical Consultant with R skills in India is ₹736118. Also, The average salary for an IT Consultant is around ₹610000 in India.
   
• R professionals are also earning a lot of money in the marketing and advertising industry. The average salary for R users in this industry is around $73,000 annually. The average salary of a data scientist in India's Marketing & Advertising field is ₹ 9.8 Lakhs per year.
   
• An R programmer can earn up to $86,000 per annum in the financial services market. In India, the salary of a finance professional can go up to ₹16 Lakhs per annum.
   

It is important to note that the market trends can evolve. Thus, staying updated and informed about the market trend for R users is advised.

Essential R Skills

If you are learning R, then you only require basic knowledge of statistics and maths. Further, learning R will become easy and fast if you know any programming language.

The job requirements for R are varied as per the specific job role and industry. However, below are some of the most common skills for all the job roles related to R.

• Basic knowledge of statistics and maths as you will need these skills a lot.
   
• You should be proficient in the R language and must have a strong hold on it.
   
• A good grip on data visualization using packages like ggplot2, plotly, and lattice.
   
• Overall knowledge of SQL queries and databases.
   
• Problem-solving skills and analytical thinking with strong communication skills.
   
• It is advised to have a good idea of various graphs and reporting tools.

Roles and Skill Sets

R provides a wide range of job roles in the field of data science and data analysis. Below are a few job roles and their key skill sets in R.

R Programmer

R programmers are responsible for writing R code for data analysis and modelling. They are in charge of creating tools that will ease the process of data analysis. They use various data structures to make the development process quick and effective.

The skill set of an R Programmer includes the following:

• Proficient in R language
   
• Statistical analysis and Data visualization
   
• Machine learning
   
• Data Wrangling

Data Scientist 

Data scientists gather and analyze large sets of raw data and turn them into valuable data for making decisions. They analyze, process, and model data to create tools that help predict the accurate future. They should mine, clean, and present data and possess analytical and business skills.

The skill set of a data scientist includes the following:

• SQL, R, Python, and a few libraries in Python (Pandas, Numpy, Scikit Learn, and TensorFlow).
   
• Data visualization tools like Tableau/Power BI.
   
• Proficiency in R.
   
• Knowledge of tools and packages like caret, tidymodels, and MLR.

Data Analyst

A Data Analyst is in charge of solving various types of business issues. They collect data from multiple sources and utilize it to make better business decisions. A data analyst examines data to find customer insights and potential uses for the info. 

The skill set of a data analyst is as follows:

• Proficiency in R.
   
• Solid understanding of statistical concepts and techniques.
   
• Knowledge of packages like dplyr and tidyr.
   
• Knowledge of data visualization libraries like ggplot2 and plotly.
   
• A good understanding of data modelling.

Data Architect

A data architect is in demand in many domains. He is responsible for integrating and maintaining their data sources. These data sources must align with the latest techs like Spark to stay relevant.

The skill set of a data architect is as follows:

• Proficiency in R.
   
• The fundamentals of data management, database access, and management.
   
• Knowledge of the IT environment of the company, including the use of database products, APIs, query languages, etc.

Data Engineer

Data Engineers make data more usable for companies to review, analyze, and enhance their performance. Their work mainly entails building new systems that collect, handle and turn raw data into proper forms.

The skill set of a data engineer includes the following:

• Knowledge of Data Warehousing, custom ETL design, and data pipeline.
   
• A good understanding of schema design, data architecture, and data modelling.
   
• Experience with database management and SQL queries.

What is the salary trend for R?

Now that we are aware of various roles in R and their skill sets. Let us now see the salary trend for various job roles in R based on major parameters.

Based on Job Roles

Let us now look at different job roles and their salaries for R users. 

**The salary mentioned above is only an estimate. The actual salary may vary.**

Based on Experience

Given below are the salary for different job roles of R as per the years of experience.

**The salary mentioned above is only an estimate. The actual salary may vary.**

Based on Companies

Now let’s see the average salary of R-related roles in a few companies in India.

List of Companies Hiring for R Programmers in India:

**The salary mentioned above is only an estimate. The actual salary may vary.**

Future of R Programming

There is no doubt that the future of R programming is bright as it is the most demanded language for data scientists and data analysts. R is utilized in most sectors like banking, social media, healthcare, finance, e-commerce, and much more. Due to higher demand and a lesser supply of talented minds, this industry provides a place for both professionals and novices.

Further, R is continuously expanding, and people all over the world are contributing to its growth. So it would be correct to say that R has a very bright future, and now is the time to start your career in this industry.

Frequently Asked Questions

Is there a demand for R programmers?

Yes, there is a huge demand for R programmers in the market, and it is expected to grow even more.

Which is better for data analysis, R or Python?

R is better compared to Python for data analysis purposes. Python is not specialised as R in terms of statistical calculations.

Is learning R easy?

Yes, learning R is quite easier if you have a basic knowledge of other programming languages. However, Python is more simple to learn than R, but R is preferred as it provides better features for data analysis.

Do we need prior knowledge of any programming language for R?

Yes, a basic understanding of programming is required to learn R. It would make your learning far easier.

Can I become an R programmer with no experience?

One can become an R programmer without experience, but one must have the necessary skills. Also, experience with deployed projects is quite helpful in order to get hired without training.

Conclusion

This article discusses the Salary trend of R users. We discussed various job roles and their skill set, and the average salary in India. We hope this blog has helped you enhance your knowledge about the salary trend of R users. If you want to learn more, then check out our articles.

• Features of R
• R Programming Interview Questions
• Advantages of R Programming
• Resume for software engineer fresher
   

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