Data Science

What Are Today’s Data Scientist Salaries Like?

Written byJohn Terra
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Updated onJuly 24, 2023

We live in a data-focused world, where knowledge is power, and information is the lifeblood of today’s economy. Organizations with the correct data can improve their chances of succeeding and thriving, avoiding costly mistakes, and delivering the best returns on investment. These reasons are why data scientists are in great demand.

This article focuses on a typical data science salary today, breaking the information down by nation, company, industry, experience level, and other factors. We will also talk about what a data scientist does (as opposed to a data analyst), the roles and responsibilities of the position, the required skills, and how to improve your data science skill set.

Let’s start the journey by describing what a data scientist is and what they do.

What is a Data Scientist, and What Do They Do?

Data scientists are analytics professionals responsible for collecting, analyzing, and interpreting data that drives an organization’s decision-making. Data scientists combine elements of various traditional technical jobs such as computer programmer, mathematician, scientist, and statistician. The position involves using advanced analytics techniques like machine learning and predictive modeling and applying scientific principles.

As part of their vocation, data scientists often use vast amounts of data to develop and test different hypotheses, draw inferences, and analyze information like cybersecurity threats, customer and market trends, financial risks, stock trades, equipment maintenance needs, and even medical conditions.

In commercial areas, data scientists typically mine data for information used to predict customer behavior, detect fraudulent transactions, identify new revenue stream opportunities, and fulfill other business needs. Data scientists also do critical analytics work for academic institutions, healthcare providers, government agencies, sports teams, etc.

Also Read: What is Data Science? A Comprehensive Guide

The Specific Roles and Responsibilities of a Data Scientist

Here’s a list of specific roles and responsibilities carried out by data scientists:

Identify valuable sources of data and automate the collection process
Undertake the preprocessing of all structured and unstructured data
Analyze vast amounts of information to discover patterns and trends
Develop predictive models and machine-learning algorithms
Combine models using ensemble modeling
Present information using various data visualization techniques (e.g., charts, tables, PowerPoint)
Suggest solutions and strategies to resolve business challenges
Work with engineering and product development teams

Additionally, data scientists often find information that promotes effective marketing campaigns, more robust supply chain management, improved customer service, and better overall business decisions and strategies. Sometimes, however, organizations ask data scientists to explore data without having a specific problem to resolve, leaving it up to the data scientist to deliver insights, develop questions, and do the analysis work.

Sometimes, data scientists are asked to help define and establish best practices for data collection, preparation, and analysis. Finally, data scientists are increasingly asked to develop artificial intelligence technologies for in-house or customer use, such as AI-driven robots, conversational AI systems, etc.

Skills Required for a Data Scientist

Today’s organizations expect a lot from data scientists, so having the necessary skills to meet the challenges and demands is essential. Here is a list of skills typically found in a good data scientist. Note that data scientists don’t need to be masters of all these skills; expectations can vary depending on the organization, industry, and job title. Also, you can gain these skills through a comprehensive data science course online.

Experience in all phases of data science, ranging from initial data discovery to data cleansing and model selection and concluding with validation and deployment
The ability to aggregate data from diverse sources and prepare it for analysis
Knowledge of typical data warehouse and data lake structures
Experience using statistical approaches to solve analytics problems
Experience with public cloud platforms and services (e.g., AWS, Azure, etc.)
Proficiency with popular machine learning frameworks
Familiarity with everyday data science and machine learning techniques like K-nearest neighbors, decision trees, random forests, naive Bayes classifiers, and support vector machines
Experience in qualitative and quantitative analysis techniques
Familiarity with a comprehensive collection of data sources like databases, big data platforms, standard data formats (e.g., JSON, YAML, and XML), and public or private APIs
Experience with data visualization tools like Power BI and Tableau and data frameworks like Hadoop
The ability to conduct ad hoc analysis and transparently present the results to stakeholders
Robust math skills
Knowledge of Python, R, and SQL; familiarity with Scala, Java or C+ is a bonus
Excellent communication and presentation skills
Earning a BSc/BA in Computer Science, Engineering, or other relevant fields, preferably a graduate degree in Data Science or another quantitative field.

Now that we know what a data science position entails, let’s see how well the compensation stacks up.

Also Read: How to Become a Data Scientist in 2023?

Data Science Salaries Around the World

Here’s a sampling of average data science salaries from the top ten highest-paying countries, as reported by analyticsinsight.net:

United States. US$95,000 for an entry-level position
Switzerland. US$113,500
United Kingdom. £61,000
Australia. US$170,000
Israel. 372,000 NIS
India. US$93,680
Canada. US$94,000
China. US$98,169
Italy. US$60,000
France. EUR76,900

Data Science Salary by U.S. City and State

Not every city in the United States pays the same rate for a data scientist. Here are the top-paying US cities for data scientists, according to ZipRecruiter. Notice how California dominates the data scientist scene.

Mountain View, CA: $160,380
Santa Clara, CA: $159,129
San Francisco, CA: $156,800
Marysville, WA: $152,310
San Jose, CA: $151,842
Fremont, CA: $151,577
Oakland, CA: $149,849
FBI Academy, VA: $149,311
San Francisco Bay Area, CA: $148,077
Antioch, CA: $146,522

If California isn’t your cup of tea, let’s look at the average data science salary in other states, courtesy of ZipRecruiter.

New York: $145,027
California: $143,099
Vermont: $130,783
Maine: $129,931
Massachusetts: $128,900
Nevada: $128,653
New Jersey: $127,259
Wisconsin: $126,987
Washington: $126,680
Oregon: $125,467

Data Science Job Salary by Position

According to Glassdoor, a basic data scientist in the United States earns an average of $152,530. Senior data scientists earn $201,405 annually, and lead data scientists bring in $194,159 annually.

Data Scientist vs. Data Science Analysts

Although these two job positions are often used interchangeably, they are different occupations. Long story short, data science analysts manipulate data to create dashboards and reports, while data scientists conduct data analysis, machine learning, and software engineering. So, data scientists typically have the same skills as most data analysts, plus an additional, far more technical, skillset.

According to Glassdoor, the average data science analyst salary in the United States is $137,272. This compensation is less than Glassdoor reports for data scientists, reflecting the latter’s greater skillset.

Major Industries Hiring Data Scientists

We see data scientists in many industries, with new ones climbing on the bandwagon daily. This trend emphasizes the versatility of the information that data scientists acquire. According to Glassdoor, these are the top five industries hiring data scientists:

Information Technology. $177,425 per year, 13% higher than other industries.
Real Estate. $165,569 per year, 6% higher than other industries.
Agriculture. $162,814 per year, 5% higher than other industries.
Retail & Wholesale. $161,750 per year, 4% higher than other industries.
Financial Services. $159,862 per year, 3% higher than other industries.

Major Companies Hiring Data Scientists

Data science has applications in many types of companies. Data scientists’ information can give a company a much-needed edge over the competition. The most competent organizations realize this and offer excellent compensation to attract the best talent. Here are the top-paying companies for data scientists today, as reported by Glassdoor.

These data science salary figures are subject to many variables. The typical data science job salary can change depending on the city, the demand, and the candidate’s experience level.

Meta: $245,839 per year
Ascendum Solutions: $141,496 per year
IBM: $161,983 per year
Google: $234,157 per year
Quora, Inc.: $182,551 per year
Amazon: $205,503 per year
Oracle: $205,024 per year
Expedia Group: $184,132 per year
Microsoft: $210,804 per year
Booz Allen Hamilton: $130,782 per year
Walmart: $179,106 per year
Apple: $220,897 per year
Wayfair: $159,448 per year
Intel Corporation: $196,881 per year
Cisco Systems: $209,314 per year
Uber: $189,544 per year
Ford Motor Company: $158,815 per year
ServiceNow: $185,378 per year
Airbnb: $214,928 per year
Capital One: $159,945 per year

Data Scientist Salaries by Experience

The more experienced the data scientist, the better the data scientist’s salary. Glassdoor states this is the data scientist’s salary breakdown according to years of experience.

Entry level to 1 Year: $119,756
1-3 Years: $135,394
4-6 Years: $150,103
7-9 Years: $159,439
10-14 Years: $174,204
15+ Years: $194,802

Do You Want to Become a Data Scientist?

Whether you’re a data scientist wanting to upskill or interested in making a career change, this data science bootcamp has the critical knowledge necessary to help you have a more fulfilling career. This bootcamp teaches you to make data-driven decisions through a high-engagement learning experience. You will get six months of applied learning to equip you for a good position and a high data science salary.

Remember, data makes today’s world go round. Join this bootcamp, and get the skills you need to succeed in today’s data-intensive marketplace.