Updated June 15, 2023
Introduction to R Programming Language
Careers in R programming are associated with the data science and business analytics profession. It is a highly in-demand programming language for the data science and statistical analytics industry. Data Analysts, Statisticians, and Data scientists are the most popular job roles for skilled R programming professionals. There are several scopes for entry-level R programmers and experienced R programmers in the Data Science domain. R programmers are well paid by the organizations which deal with data science projects. R programmers are a good fit for the research-oriented industry for statistical model implementation for data analysis. professionals who want to upgrade their career in data science, R programming is a preferred choice.
Education for R Programming Language
Learning R does not require any special knowledge. To learn R, you must have basic statistical and mathematical knowledge. In addition to this, if you have a basic idea about programming languages, it will be easy for you to catch up on things in R faster. To make learning R easier, you should get started with real-life problems and then get your code reviewed against similar problems. In addition to these, you must understand various types of graphs for data representation. R is a complete package that can be used to analyze data using statistical theories. Hence, you must have these three skills to learn R easily.
- Basic statistics and mathematics knowledge
- Basic understanding of any programming language
- Knowledge of different graphs and reporting tools.
Career Path in R Programming Language
The above graph represents the increase in jobs for R programmers. R is the language that will be in boom, along with Python and Hadoop. R is being used by users ranging up to 2 million people. The careers in R programming also include machine learning and artificial intelligence. Business intelligence is also a field that has the advantages of R. Experts of trading markets can examine the trends and do research on stock markets, market dynamics, etc. Proper mathematical knowledge, financial analysis abilities, and programming experience, and needed to pursue this path.
R Programming Language Job Positions
The question arises which are the various fields that are using R and making it the hot topic it is. The careers in R Programming that can lead to your ‘R’ enlightenment are as below:
- R programmer
- Data Scientist
- Data Analyst
- Data Architect
- Data Visualization Analyst
- Geo Statisticians
- Database Administrator
- Quantitative Analysis with R
R Programmer– The job of R programmers is to use their programming skills and knock down the data and create tools that can ease the process of data analysis. They use data structures such as vectors, matrices, and data frames which help in quick and efficient development.
Data Scientist– This is one of the paths which is in demand for R programmers. A data scientist is responsible for designing and implementing layouts for large data sets, data modeling, data mining, research purposes, and prediction.
Data Analyst– A data analyst should combine technical and analytical knowledge. In addition to this, a DA should have in-depth information regarding a database system and machine learning.
Data Architect– Many domains these days are in need of data architects. Data architects integrate and maintain their data sources. They must align with the latest technologies like Spark to stay relevant. Also, a data architect must know about data warehousing solutions, database architecture, ETL and BI tools, data modeling, and system development.
Data Visualization Analyst– A data visualization analyst should be able to create and distribute interactive dashboards that will give all information to make major business decisions. They provide an extensive graphical report that helps the business in predictions and making decisions that will help the business grow.
Geo Statisticians– These professionals take responsibility for examining spatial and spatiotemporal datasets.
Database Administrator– A database administrator ensures that a database is available to all users requiring a particular data set. They ensure that all data has a backup and recovery mechanism. They also need to take care of data modeling, design, and data security and should be well-versed in the business they are involved in.
Quantitative Analysis with R– In all different domains like finance, telecom, hospitality, etc., quantitative analysis ensures that all portfolios are risk-balanced and help us in finding new opportunities and evaluating all asset prices using mathematical models.
The average salary of the R programming job of these professionals will be as follows:
- R programmer: Average salary of an R programming job is $77,722 per year. This would be around Rs 481,586 per year in India.
- Data scientist: Data is money these days. A person analyzing this data is sure to be awarded a whopping amount of $123,000 a year on average. Similarly, that would be Rs.620,244 per annum in India.
- Data Analyst: A data analyst can earn an average of $69,979 per year. Indian equivalent pay for this R programming job is Rs.349,284 per year.
- Data Architect: Data architect gets paid up to $112,764; in India, it is ₹2,100,609.
- Data Visualization Analyst: The salary for this profession is $84,809
- Geo Statisticians: Roughly, this subset of R professionals gets about $71,000 per year.
As a result of this new and niche technology, R will surely be heading all data analytics languages. Programmers should have in-depth knowledge of R Studio, Eclipse, and Visual Studio. To make it easier and reachable to as many people as possible, various online training provides insight into R. They start from the basics of R programming and progress to learning all language fundamentals, using all data concepts for analysis, and finally, expertise in R language. They also offer services in all domains, which adds to its extensibility. This is why a Career in R Programming is beneficial today due to its growing day-to-day importance.
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