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.
Read More: Data Scientist vs. Data Analyst – The Differences Explained
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?
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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.
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