What is the Best Data Scientist Salary in 2023 and How to Get it?

What is the Best Data Scientist Salary in 2023 and How to Get it? | Data Science and Analytics | Emeritus

Data scientists are famously well-paid across the globe. In fact, a recent LinkedIn report indicated that data science specialists, machine learning engineers, and artificial intelligence specialists are the top 15 in-demand and fastest-growing jobs. However, just like any other field or role, a data scientist’s salary is more of a spectrum than a bull’s eye. The average salary varies depending on a variety of factors. Additionally, the parameters that define what is a ‘high’ salary also change with factors like region, age, or educational qualifications. That said if you want to explore how lucrative this field is or understand if you’re being paid optimally, keep reading.

What is Data Science?

Data science is a discipline of applying advanced analytics techniques and scientific principles to extract valuable information from data for business decision-making and strategic planning. Needless to say, data science as a function is becoming increasingly important to businesses so that their decision-making may be informed. Additionally, there are various aspects of data science like machine learning, artificial intelligence, data mining, data engineering, and more. Check out our related post, what is data science, for a more detailed and thorough answer to this question.

What is the Average Salary of a Data Scientist?

There are many careers in data science, and the average salary will vary depending on many factors, including:

  • Experience of candidate
  • Job title/ position
  • Kind of organization
  • Geography
  • Educational background

1. A Data Scientist’s Salary Commensurates with Experience

Based on experience over several years, data scientist and their corresponding salaries can be divided into three groups:

Entry-level Data Scientist Mid-level Data Scientist Senior-level data scientist 
Experience  0-5 years 5-12 years 12-20 years
Average Salary* US $95,000 US $130,000 US $165,000

*As per the Butch-Works report released in 2020

I: Entry-level Data Scientist (0-5 years of experience)

This group includes freshers or professionals who have just started their careers. So, entry-level data scientists have a salary of around US $95,000 per annum.

II: Mid-level Data Scientist (5-12 years experience)

This group comprises data scientists who have a decade or so in the field and might be at mid-senior levels. Such a mid-level data scientist’s salary would be around US $130,000. Thus, if such a professional is already in a managerial position, his/her salary could go up to US $195,000.

III: Senior-level Data Scientist (12-20 years experience)

This group would have data scientists who have considerable experience in the field and are possibly in leadership roles. Hence, the median salary of senior data scientists would be around US $165,000. But, if such a data scientist is in a leadership role, his/her salary could go up to US $250,000.

Pro Tips

  • ‘Experience’ can be calculated not just in the number of years but also in the density and depth of a data scientist’s knowledge.
  • The number of years of experience cannot be taken arbitrarily, you have to consider relevant experience only
  • Not all managers earn more than individual contributors; for some niche roles, skilled individual contributors can make more than managers do
  • Salaries vary according to roles too. For instance, data mining roles might not make as much as data engineering roles

Next promotion is a course away

2. Do Job Titles Have a Role to Play in a Data Scientist Salary?

Data science is not a single role but a collection of different roles that have varying functions. So, a data scientist’s job title can depend on years of experience, skill sets, or the type of organization he/she works in. In essence, specific job titles have an impact on the data scientist salary per month.

Here is a representation of different data scientist roles and how the salaries vary for each of them.

Job Title

Average Salary*

Data engineer or architect

US $112,493

Data analyst

US $69,517

Data scientist

US $117,212

Machine learning engineers

US $131,001

Big Data Engineer

US $104,463 

Chief Data Officer

US $146,133

*As per Glassdoor

ALSO READ: Top 9 Roles to Pursue a Career in Data Science in 2022

Pro Tips

  • Beginners usually start as data science interns, junior data engineers, or junior data analysts
  • Each of these roles can be pursued after a certain amount of experience
  • These roles also require different skill sets. For instance, you need to know Machine Learning to be a Machine Learning Engineer

3. Do Startups Pay Pata Scientists More Than Large Companies?

Top 10 Companies That Have the Best Pay for Data Scientists


Average Salary

(in the US)*


US $178,030


US $164,372


US $162,802


US $159,575 


US $145,172


US $148,660


US $136,741


US $134,845


US $126,298


US $123,655

*As per, Indeed.com

Are you wondering how salaries are impacted by the type of organization? Well, in a large multinational organization, you might be an individual contributor data scientist even with 12 years of experience. But, in a startup, you can be Chief Technology Officer with the same number of years. The size and the type of organization affect how much employers are willing to pay for their resources.

The consensus is that the larger the company, the better the pay. An article by the University of Wisconsin states that a company with 10,000 employees will pay more than a company with 1,000 employees. The same has been reiterated in the O’Reilly Salary Data Science Salary Report, 2016. This means that a startup will pay data scientists the minimum, then come larger startups or ‘unicorns’ as we call them these days, then come mid-sized companies, and the highest salaries will be paid by large organizations. This gradation of pay can be simply explained by the fact that large organizations have higher budgets to pay for resources than smaller companies.

Pro Tips

  • Large companies have a structured approach to salary or set pay scales. Hence, negotiating salaries beyond a point may not be fruitful
  • Data scientists must use their powers of persuasion when applying to startups, which have more fluid structures, but also be prepared for a dynamic setup and instability
  • Typically, startups or smaller companies offer lower base salaries and higher performance-based incentives
  • Startups also tend to give better hikes than large organizations as they are not bound by structured appraisal slabs

4. Does Your Location Change the Numbers on Your Paycheck?

The short answer is yes. Essentially, the standard of living of the region one belongs to plays a part in determining pay packages. Moreover, certain countries have labor laws that set minimum wages for certain roles, and employees have to be paid accordingly. So, a data scientist’s salary will be subject to the rules and regulations, taxes, and the standard of living of the country he/she is based.

The following are the top 10 countries where data scientists are paid the highest salaries:


Average Salary*

United States

US $120,000


US $111,000


US $88,000


US $77,870


EUR 9,470 


US $75,000


JPY 825,000

United Kingdom



EUR 8,930


EUR 76,900

*As per Analytics Insight

5. Do Your Educational Qualifications Impact the Data Scientist Salary?

Does your alma mater have a role to play in how much money you will make? Well, yes to a great extent. Your educational qualifications make a difference at the entry level when you have no other skills to be judged by except your degree. Eventually, your skills matter just as much as the degree. Some companies only recruit graduates from Ivy League schools, but they are few and far in between.

Frequently Asked Questions About Data Scientist Salary

#1: What are the top companies that hire data scientists?

Data scientists find employment in a wide range of companies and industries. However, we look at companies in terms of scope, job openings, and the average salary being offered, then the following the list to be considered:

  1. Pinterest
  2. Snap
  3. Microsoft
  4. Accenture
  5. Oracle
  6. Slack
  7. Lyft
  8. Intel
  9. Uber
  10. Crayon Data

#2: What are the popular skills required to become a data scientist?

Having a degree or certification in data science is only the first step. When companies hire resources, they look at usable skills as a top priority. Chicago-based data analyst and blogger, Rashi Desai who writes the popular blog Towards Data Science have listed the top 10 skills that make data scientists employable:

  1. Probability and statistics
  2. Multivariate calculus and linear algebra
  3. Programming packages and software: Python, R, SQL, Java, Julia, Scala, MATLAB and TensorFlow (great for Data Science in Python)
  4. Data wrangling
  5. Database management
  6. Data visualization
  7. Machine learning / deep learning
  8. Cloud computing
  9. Microsoft Excel
  10. DevOps

#3: Which industries have the highest demand for data scientists and which among these pay the highest salaries to data scientists?

As per the well-known data science blog Galvanize, the following industries have the highest demand for data scientists in terms of volume:

  1. Finance and insurance
  2. Professional, scientific, and technical services
  3. Information technology
  4. Management of companies and enterprises
  5. Manufacturing
  6. Utilities
  7. Wholesale trade
  8. Mining, quarrying, and oil and gas extraction
  9. Public administration
  10. Agriculture, forestry, fishing, and hunting

According to the same source, the industries that pay the highest data scientist salaries are:

  1. Finance & Insurance
  2. Professional Services
  3. Manufacturing

Data science is an evolving field where new tools and technologies sprout quickly. Naturally, how much you know about data technology matters. The good news is that you can brush up on the skills as well as the educational qualifications if you choose to study online.

Emeritus offers a whole range of data science courses that can help you move up the ladder as a data scientist.

For content collaborations and feedback, write to us at content@emeritus.org


About the Author

Content Writer, Emeritus Blog
Sanmit is unraveling the mysteries of Literature and Gender Studies by day and creating digital content for startups by night. With accolades and publications that span continents, he's the reliable literary guide you want on your team. When he's not weaving words, you'll find him lost in the realms of music, cinema, and the boundless world of books.
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