Data Science Salary: Based on Location, Company, Experience

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30th Nov, 2022
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12th May, 2022
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Data Science Salary: Based on Location, Company, Experience

Data science is a discipline that combines subject-matter expertise, programming prowess, and knowledge of mathematics and statistics to derive practical insights from data. Artificial intelligence (AI) systems apply machine learning algorithms to text, numbers, images, videos, music, and other types of data to produce tasks that would typically need human intelligence. These technologies generate insights that analysts and business users can use to generate substantial economic value. 

The first step of the data science pipeline workflow is data collection, from which data is occasionally extracted and entered into the system. The maintenance stage includes data warehousing, data processing, data cleansing, data architecture, and data staging. 

In this article, we will learn more about data scientist salaries based on several aspects. Prior to that, we'll learn more about what a data scientist is, their roles and responsibilities, the skills needed, and other topics. Let's explore a data scientist's average salary with regard to various aspects. You can check out the Best Data Science Certifications online to learn more about the domain and get certified to land your dream job. 

Who Is a Data Scientist?

Data scientists are experts who find, collect and evaluate big data collections. You can understand how important data scientists are to any firm, given that today's business choices are driven by insights obtained from data analysis. Computer science, mathematics, and statistics training are often required for data science positions. Data scientists do more than just model and process structured and unstructured data; they also translate the results into useful strategies for stakeholders. 

Data scientists are very knowledgeable in math and statistics, and they also have a strong grasp of ideas such as big data, machine learning, data mining, deep learning, and data warehouses, among others. They also have a perfect command of statistical software and programming. The duties of a data scientist go beyond just processing and analyzing data.  

Business analysis and data science responsibilities often overlap because data science roles differ from organization to organization. Expert data scientists typically have extensive industry knowledge and years of expertise. Data scientists are among the highest-paid workers on the market because of how they collaborate with several stakeholders and support important business decisions. 

Data Science Salary in 2023

Data scientists work on a variety of data-driven initiatives where they are involved from beginning to end. The need for qualified data scientists is growing, and they may now command high pay as they handle everything from data collecting to sharing insights with management and stakeholders. 

Data scientists' pay depends on a number of variables, including their experience, work location, skill set, industry, and company. The post will go through the aforementioned elements and assist you in making the best decision before deciding on a data scientist job. To make it easier for you to explore, we have divided the article into the sections listed below.

Data Science Salary: Based on Experience

Young IT workers are especially drawn to careers in data because of the significant correlation between years of experience and higher-paying salaries. In this section, we'll examine how the pay for data scientists increases with experience. Let's check the data scientist's starting salary and the senior data scientist's salary.  

The average data scientist's salary per month is $7,111

  • Entry-Level Data Scientist Salary 

Let's check entry-level data science salary or a junior data scientist's salary. Every profession starts at the entry level, and data scientists are no exception. Most often, entry-level data scientists are those who have recently graduated from college or are changing careers and are completely new to this sector. It is also crucial to talk about the entry-level pay for data scientists because it impacts the median pay for the field.  

An entry-level data scientist's salary is $84,418 annually. 

  • Intermediate-Level Data Scientist Salary 

Intermediate-level data scientists are those with between one and four years of experience. The salaries of this group, which includes the majority of data scientists, can be used as a benchmark whenever the topic of a data scientist's salary is brought up. These data scientists are typically on their way to becoming senior data scientists and have experience working on both challenging and essential data science projects. An intermediate-level data scientist makes an average salary of $115,729 annually. 

  • Senior Data Scientist Salary 

 A highly skilled data scientist with decades of experience or managerial positions earns significantly higher. A senior data scientist's salary is $138,061 annually.  

Data Science Salary: Based on Location

Professional salaries can be high in some places for a variety of reasons, including the presence of high-tech businesses, large cities, expensive living expenses, etc. Additionally, there are some cities that draw in highly trained workers. As a result, businesses that wish to hire or keep highly skilled workers provide competitive salaries and perks.

CountryAvg. Salary Per Year
India₹ 10,60,000
US$100,431
UK£50,606
Australia$122,674
Canada$86,359
Singapore$104,532  

Check out the Online Data Science Bootcamp to build analytical skills and programming knowledge and advance your career in the domain. 

Data Scientist Salary by Job Title

  • Data scientist 

Data scientists are in charge of supporting organizations with data acquisition and data sourcing. Professionals in data science assist with processing, cleaning, integrating, and storing data. Data scientists are primarily responsible for investigating data and carrying out exploratory data analysis. Additionally, they create data models and make recommendations for algorithmic approaches to data use. Data Scientists are sometimes in charge of utilizing machine learning to utilize the data or combining it with AI systems.  

Data scientists must be proficient in Python, R, or Scala programming. Additionally, they must be familiar with NoSQL DBMS systems, distributed file systems like Hadoop, and RDBMS like MySQL, MariaDB, and others. Data scientists must also have a solid understanding of data visualization. A data scientist makes an annual income of approximately $100, 431, while a chief data scientist's salary is $142,811.  

A data science consultant's salary is $126,050 annually. 

  • Data Analyst 

Data analysts are in charge of data analysis and report preparation for their organizations. Database management and data collecting system integration are additional tasks assigned to analysts. For the most part, analysts employ statistical tools and prediction techniques to find, analyze, and interpret trends or patterns in datasets. 

Data analysts need to be proficient with programs like Microsoft Excel, Tableau and all-encompassing office suites like Microsoft Office. A data analyst, for instance, might be proficient in the Microsoft ecosystem, which includes Azure, Power BI, and Access.  

Data analysts must be proficient at creating reports and giving presentations. It is crucial for organizations to extract the most important information from enormous datasets. Data analysts must therefore be proficient with SQL and a variety of database management systems. Data analysts must also use data visualization. A data analyst makes an annual salary of $65,934

  • Data Science/Analytics Manager 

They have one to three direct reports, are well-versed in technical and mathematical concepts, and have a proven knack for leadership and business. Data science/analytics managers increase the usability and accessibility of data for organizations. They are responsible for facilitating an organization's data infrastructure and enabling systems to utilize this data. Additionally, this implies that data engineers are in charge of integrating cloud services and outside applications with data models or systems. 

The creation of algorithms that aid in making raw data understandable for businesses is another responsibility assigned to experts in this field. In addition, data science/analytics managers need to comprehend an organization's data needs and find answers to key data-related concerns. A data science manager's salary is $149,503 annually.  

  • Big Data Engineer 

The rise of data volumes has also been facilitated by the introduction of cloud databases and technology. Businesses benefit from the integration of big data with cloud computing and other cutting-edge technology. As a result, the need for Big Data Engineers has greatly increased. 

Big data engineers are experts who are in charge of creating, managing, testing, analyzing and interpreting the data of an organization. Big data refers to the enormous quantity of data sets that businesses amass through routine business activities. An organization's productivity, profitability, and scalability can be increased by using the useable sets of data that a big data engineer extracts from data processing systems and databases. The average salary of a big data engineer is $109,481 annually. 

How To Improve Data Science Salary?

Your ability to make earnings as a data scientist might be considerably impacted by your job choice. Generally speaking, working for major MNCs will allow you to earn more money than working for a smaller company. The organization you work for, however, is not the only factor that can affect your data scientist compensation. Your ability to generate more money can also be increased by taking on more responsibility. 

Every time you advance from a Level 1 data scientist to a Level 2 data scientist, and so on, you can often anticipate a pay raise. Additionally, managing data scientists frequently involves managing people, which generally results in higher pay. 

1. Skills

You can't afford to let your skill set stale out. For greater professional opportunities, you must always be a go-getter and upgrade your skills! Certain skills that aid a company in improving its operations are sought after by employers. There is a reason why having a skill set is important. Data science requires a variety of abilities, which reduces the amount of time it takes to complete tasks. Knowledge of these skills also helps one solve problems. Along with hard skills, soft skills let professionals think creatively and work more effectively for improved customer satisfaction. 

2. Certifications

Due to the difficulty in locating qualified candidates with the ideal combination of education, training, experience, and abilities, businesses face a shortage of these specialists, which contributes to the high competition in their pay scales. The industry offers countless opportunities, and jobs in data science promise a wealth of opportunities and great compensation. Your career will advance, and you will get first-hand experience with key technologies like R, SAS, Tableau, Python, and Hadoop. Enroll immediately to learn data science and enter the fascinating world of data. 

3. Degrees

The most likely prerequisites for becoming a data scientist are a bachelor's degree and coding proficiency. However, a lot of data scientists earn their PhDs and master's degrees. The higher your level of education, the higher your expected salary level. A master's degree in data science could be quite beneficial for you if you want to be a competitive candidate in this profession. A master's degree could help you advance in the field of data science by helping you get hired at your ideal organization or get promoted. 

4. Experience

One of the most important criteria that determine the ultimate salary is experience. The ability to develop more workable solutions, having more in-depth knowledge, operating agility, and better leadership qualities all increase with experience in the sector. You'll probably earn more money as a data scientist the more experience you have.

How Much Can You Make as a Data Scientist?

How much do data scientists make? Data Science offers a huge range of applications, and with the quick uptake of big data ideas and technology, more businesses are in desperate need of qualified Data Science specialists. While some organizations use data for insights, some businesses use enormous amounts of data directly to run their day-to-day operations or to support their services (or applications). Data is a critical tool for businesses of all types to use when making decisions. As a result, experts in data science are needed by all kinds of businesses. 

It's no secret that data scientists can add tremendous value to a position. However, it can be difficult to locate just one person who is capable of performing all the duties expected of a data scientist, and there is intense rivalry for these positions. Employers are, therefore, willing to pay huge compensations to skilled and experienced data scientists. Thus, a data science job's salary is comparatively higher than other job roles. 

Conclusion

The job description and pay for data scientists are highly attractive. It's time if you believe you possess the necessary aptitude and zeal to pursue a career as a data scientist. To enter the world of data science, you can also think about taking some pertinent data science courses based on your degree of expertise and skill. Opportunities abound, and the market requires qualified professionals. Enroll in the KnowledgeHut Best Data Science Certification and learn to tackle complex Data Science problems by acquiring skills across programming languages and technologies from industry experts.

Frequently Asked Questions (FAQS)

1. Is it hard to become a data scientist?

Data Scientists need to have extensive knowledge not only of ML and programming but also statistics and mathematics. It can be pretty tough to become a data scientist, but with the right training, it is not too difficult.

2. Can I learn data science in 1 month?

Even if you have extensive knowledge about all the related fields, you need more than a month to learn data science. 

3. Where do I start with data science?

You can start learning data science on online training courses and also do research about the subject yourself. 

4. Which skills are required for a data scientist?

Some of the required skills of a data scientist are- ML, Programming, and Mathematical and Statistical Analysis. 

5. Does data science require coding?

Coding is important in data science, but you do not need to be a coder. Knowing one of two languages is enough. 

6. What is the highest salary in data science?

The Highest salary in Data Science is INR 25.0 Lakhs per year. 

7. How much money can you make in data science?

The median income for a data scientist is INR. 698,412. An entry-level data scientist with less than a year of experience makes around INR 500,000 per year. Data scientists with 1 to 4 years of experience make around INR 610,811 per year. 

8. Is data science in high demand?

Data scientists are in high demand as data can be used for different purposes. Data Scientist jobs have grown by 650 percent, and this trend shows no signs of slowing down. According to the U.S. Bureau of Labor Statistics, demand for data science abilities will rise by 27.9 percent by 2026. 

Profile

Mounika Narang

Author

Mounika Narang is a project manager having a specialisation in IT project management and Instructional Design. She has an experience of 10 years 
working with Fortune 500 companies to solve their most important development challenges. She lives in Bangalore with her family.