A decade ago, Harvard Business Review (HBR) dubbed data science “The Sexiest Job of the 21st Century.” They went on to mention that there was a shortage of data scientists in many sectors, which meant the demand for these professionals would increase. Moreover, according to HBR, data scientist salaries would be highly competitive - even the ones at smaller companies and startups.
Ten years later, the industry has evolved. There has been an exponential increase in the amount of data generated by businesses, leading to more demand for different types of professionals within the field. Roles have been developed for data engineers, machine learning engineers, and analysts.
This shift has led many people to ask if data science was still a career worth pursuing in 2023 and whether the field would pay as well as it did before. There has also been some concern about the increase in competition in data science, as some people believe that the industry has become highly saturated.
In this article, we will walk you through the salaries of data scientists around the world. We will also break these salaries down by industry, skills, and job level. We’ll help decide whether it is still worth becoming a data scientist in 2023 based on where you live. You can also find out about data analyst salaries around the world and the top data analyst careers in separate articles.
Data Scientist Salaries by Country
Let’s start by breaking down how much data scientists get paid in different countries. It’s worth noting that salary data can be difficult to represent accurately, given that they can vary massively depending on the role, organization, and individual. Even within a country, salaries can vary greatly, and data may not always be representative. However, we’ve cited our sources and suggest looking at a range of roles in your area if you’re applying for data scientist jobs. All salaries are given in the local currency.
Average Annual Data Scientist Salary
Average National Annual Salary
The average base annual salary of a data scientist in the United States is $102,988. This is almost double the national average of $55,640 annually. In comparison, software engineers average $90,388 annually, and computer scientists are paid $95,136.
Let’s break this down by state.
Data scientists in the UK are also paid significantly more than skilled professionals in other fields. The average data scientist's income in the UK is £50,362 annually.
London is the highest-paying city in the UK, with an average salary of £59,346 annually. This is followed closely by Edinburgh, where data scientists are paid £58,558, and Cambridge, with a base pay of £54,915.
The demand for data scientists in India is at an all-time high. Analytics Insights states that India will capture 32% of the big data market worldwide and generate USD 20 billion by 2026.
The average base pay for a data scientist in the country is ₹12,88,691, although this number varies by company and job seniority. According to Indeed, senior data scientists can earn up to ₹17,30,524 annually.
The average data scientist's salary in Canada is approximately around $103,623 per year, which is 25% higher than the national average. Toronto is the highest-paying city in Canada for data science, with an average base salary of $134,302.
Data scientist salaries in Australia are generally very high, with an average base salary of $121,801 per year. This is almost double the national average of $68,298 annually, making Australia one of the best places to become a data scientist.
Data scientists in Germany earn around €64,000 each year, which is higher than the national average of €44,074. Data scientists make more than other technical professionals like computer scientists, who earn €37,227, and software engineers, who make €60,000 annually.
According to the Robert Half Salary Guide, data scientists are now one of the top five in-demand hiring roles in Singapore. Data professionals in the country are rewarded handsomely since many of the world’s top tech firms reside there.
Data Scientist Salaries at Top Companies
Salaries at top tech companies like Netflix, Google, and Meta are always higher than the average market rate. Here is a list of data science salaries in these firms:
According to Glassdoor, the average salary of data scientists at Netflix is $138,271. This is much higher than the national average salary in the US. Furthermore, this is just the base salary, on top of which Netflix employees get to enjoy benefits like bonuses, flexible working hours, paid parental leave, free rideshare services, and a stock option program.
Data scientists at Meta are paid even more than those at Netflix, with an average salary of $143,638 per year. Recently, the organization has also opened up remote work to employees at all levels. They have even started providing employees with the opportunity to relocate and work from different countries, allowing for greater job flexibility than ever before.
Google pays data scientists approximately $139,070 annually. While Google does not allow complete remote work as Meta does, the company still offers some lucrative benefits such as bonuses, financial coaching, a hybrid work model, educational reimbursement, and well-being classes.
Data scientists at Apple earn $138,094 each year. Just like Google, Apple has also adopted a hybrid-work model allowing for better work flexibility. The company also provides employee benefits such as stock grants, reimbursement of tuition fees, discounts on Apple products, flexible medical plans, and free online classes.
Microsoft pays data scientists approximately $138,464 annually. On top of this, employees also get benefits like remote work, flexible work schedules, financial assistance for tuition expenses, stock purchase plans, a loan refinancing program, and employee resource groups.
Data Scientist Career Progression
If you apply for a data science job after completing your education, you will typically be hired as a junior or mid-level data scientist depending on the company. As you gain more seniority, you will progress into more mature roles and eventually lead a data science team.
Here is what the career progression of a data scientist looks like:
Data Scientist / Junior Data Scientist
If you are just starting out and don’t have a Master's degree or a PhD, you are likely to be hired as a junior data scientist. Here, you will shadow seniors in the team and learn to apply data science techniques to solve business problems.
The estimated salary of a professional at this level is $102,988, although this can vary based on education level and previous work experience.
Senior Data Scientist
After around 3-4 years of experience in the field, data scientists typically get promoted to a senior position. They are given more responsibility at this stage and should be able to implement end-to-end projects themselves.
The estimated median salary of a senior data scientist is $128,225.
Data Science Manager
Senior data scientists move on to become managers after around 5-7 years of working in the industry. Managers shoulder the responsibility of supervising teams and overseeing the completion of data science projects.
On average, data science managers are paid $142,891 annually.
Principal Data Scientist
Principal data scientists are the highest-ranking data scientists in a company. They manage junior and senior data scientists and oversee the direction of the entire team. It can take up to 10-12 years for employees to become principal data scientists.
Principal data scientists make approximately $170,345 annually.
Salary Comparison Between Data Science Roles
Let's explore how data scientist salaries compare to other jobs in data science.
Data Scientist vs Data Engineer
Data Scientist vs Data Analyst
Data analysts are paid considerably lower than data scientists, according to Glassdoor, with an annual salary of $72,332.
However, this number is skewed as many analysts solely work with Excel files and are unable to code. If you pick up skills like SQL and Python programming as a data analyst, your income will increase.
For example, data analysts at Google earn approximately $99,990 annually, which is lower than their data scientist and data engineer salaries, but far higher than the national average.
Data Scientist vs Machine Learning Engineer
According to Glassdoor, the base salary for a machine learning engineer is $108,174. Surprisingly, this is higher than all other data-related roles we have covered so far, indicating that ML engineers are in demand.
Google pays its machine learning engineers approximately $141,398, which is also slightly more than their data scientist and data engineer salaries.
Read our article on how to become a machine learning engineer to learn more about the profession, why it pays so well, and how you can pursue it.
How to Become a Highly Paid Data Scientist?
Step 1: Expand Your Skill Set
According to Sachin Gupta, co-founder and CEO of developer hiring platform, HackerEarth, data scientists must master the following skills to get hired and negotiate for a higher salary:
- Machine learning: Data scientists must be able to build predictive models and apply them to real-world datasets. The Machine Learning Fundamentals course will teach you to do this with Python.
- Statistical analysis: As a data scientist, you should be able to analyze and interpret data to uncover meaningful insight. You can learn to do this with the Statistics Fundamentals career track.
- Python or R programming: To learn how to code fluently, take the Python Programming or R Programming course.
- SQL: SQL is a requirement in around 65% of all data science job listings. You can take the Introduction to SQL course to learn the language.
- Cloud tools: Many data scientists at corporate companies are required to access and manipulate data stored on the cloud. You can take the Understanding Cloud Computing course to learn about how the cloud works.
Step 2: Get Certified
Becoming a certified data scientist will increase your chances of landing a job and getting paid more. We offer a Data Scientist Certification program that will assess your ability to solve data science problems. This is a great way to prove your data science knowledge to hiring managers.
Step 3: Build Portfolio Projects
Finally, you need to show potential employers that you are capable of completing an end-to-end data science project. High-quality, creative projects will impress hiring managers and help you stand out from other applicants, giving you the ability to negotiate for a higher salary than everyone else.
If you don’t know where to start, here are some Python project ideas you can refer to.
Data Scientist Salary FAQs
What is the average salary for a data scientist?
According to data from Glassdoor, the average base annual salary of a data scientist in the United States is $102,988.
How does experience affect a data scientist's salary?
Generally, the more experience a data scientist has, the higher their salary will be. Junior data scientist with less than one yea rof experience can expect to earn an average of around $102,988 per year, while those with 10-12 years of experience could earn as much as $170,345 as a principal data scientist.
Does location affect a data scientist's salary?
Yes, location can have a significant impact on a data scientist's salary. Data scientists in major tech hubs such as San Francisco, New York, and Seattle tend to earn higher salaries compared to those in other parts of the country.
Do certain industries pay data scientists more than others?
Yes, certain industries tend to pay data scientists higher salaries than others. Data scientists who work in the finance and insurance industries, for example, tend to earn higher salaries compared to those who work in other industries.
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