Introduction
Data scientists were named as the third-best job in America by Glassdoor in 2022. There are many well-paying jobs in this field for someone who enjoys using data analysis to find trends and find solutions to issues. The need for individuals who can work with that data will continue to increase as our globe continues to create more data than ever before. But, you must compensate data scientists adequately in order to attract them. Also, data science salary in USA might differ by employer and state, adding extra factors to the search. So, looking for the highest-paying data scientist employment might be a difficult undertaking. But stay upbeat because assistance is on the way. This article might help you learn how much a data scientist makes and how to improve your pay in this position.
What is a Data Scientist ?
Every day, businesses produce enormous volumes of data. Everything from customer information to inventory monitoring is included in this data. Data scientists are responsible for managing this data and turning it into knowledge that businesses may use to make important choices. Their primary duties as employees are:
- They are in charge of detecting data analytics-related issues as well as chances to turn that data into useful information for the organisation.
- Searching for patterns and trends in raw data.
- Gathering, purifying, and validating data to make sure it is correct and comprehensive.
- Creating models and algorithms, then using them on the data mining.
- Analysing the raw data to find the answers, then communicating those solutions to the stakeholders
How Much Do Data Scientists Make?
The typical annual pay for data scientists in the US is $125,053 as of January 2023 . This sum consists of an annual reported supplemental pay of $21,913 and a base salary of $103,140. Bonuses, commissions, and profit sharing are all forms of additional compensation. The average yearly wage for data scientists, according to the US Bureau of Labor Statistics (BLS), is $108,660. According to the BLS, employment of data scientists and other computational and data research specialists is predicted to increase by 22% between 2020 and 2030. It is true that this pace of job growth is far faster than the 8% national average for all professions. A data scientist salary in USA depends on several factors:
1. Data Scientist Salary by Experience
One of the key determinants of a data scientist's income, according to O'Reilly's 2016 Data Science Salary Study, is experience. Data science experts typically earn $2,000 to $2,500 extra for each year of expertise. According to a 2020 Burtch-Works analysis on data science compensation, the following are the most recent trends in experience-based pay:
- Entry-level data scientist salary - The typical starting wage for a data scientist is still high at $95,000, despite the recent inflow of early-career professionals.
- Mid-level data scientist salary - A mid-level data scientist makes $130,000 a year on average. The typical compensation increases to $195,000 if the data scientist additionally holds administrative responsibilities.
- Experienced data scientist salary - Experienced data science workers make a median pay of $165,000, and experienced manager-level professionals get a significantly higher median compensation of $250,000.
2. Data Scientist Salary by Job Title
According to O'Reilly's data science pay study, 45% of individuals polled claimed to be "data scientists." Another 31% identified themselves as being in senior management, a developer, programmer, or other. Data science specialists will often earn more money if they do more managerial duties, such as managing team projects, finding business issues that may be resolved using analytics, or interacting with third parties.
- Data scientist - According to datajobs.com, individuals with the title "data scientist" are often seasoned, expert-level employees in data-driven enterprises. Their salary range is between $85,000 - $170,000.
- Data analyst - Data analysts have a hands-on approach to working with data and are frequently in a stage in their employment where they are concentrating on acquiring data science tools and skill sets. Their salary range is between $75,000 - $110,000.
- Data science/analytics manager - They have one to three direct reports, excellent technical and mathematical abilities, and a proven capacity for leadership and business acumen. Their salary range is between $90,000 - $140,000.
- Big data engineer - By developing the platforms and apps that data scientists use to execute data analytics, engineers may solve issues and provide business value. Their salary range is between $115,000 - $165,000.
3. Data Scientist Salary by Industry and Company Size
The industries with the highest median data science salaries are:
- Cloud services, hosting, and CDN
- Search and social networking
- Banking and finance
The fact that just 12% of data scientists polled by O'Reilly in 2016 worked in these three sectors is significant. Around 30% of respondents worked in consulting or software (SAAS, web, and mobile). It may come as no surprise that some of the top paid data scientists work for prestigious IT firms. These prominent companies typical wages are as follows:
| $152,856 | |
| Apple | $145,974 |
| $135,360 | |
| $134,715 | |
| PayPal | $132,909 |
| Airbnb | $127,852 |
| Microsoft | $123,328 |
In terms of business size, remuneration increases with the size of the firm. For instance, a data scientist at a firm with at least 10,000 people would probably make more money than someone in the same position in a company with less than 1,000 employees.
4. Data Scientist Salary by Region
The location where a data scientist resides has a significant impact on their salary. California, where the bulk of the data scientists polled by O'Reilly work, likewise has the highest earnings. Despite having fewer data scientists than the majority of the nation, the Pacific Northwest pays the second highest wages.
5. Data Scientist Salary by Education
Particularly when it comes to possessing the ideal mix of training and expertise, data scientists are uncommon. Data scientists must have a fundamental understanding of coding. In actuality, data scientists who code four to eight hours per week get the greatest incomes, while those who don't code at all earn the lowest.
Factors That Can Influence Data Scientist Salary in USA
The lowest end of the wage scale for data scientists, according to Glassdoor, is $78,000 annually. $204,000 is the top end of this wage level. Your compensation as a data scientist in the US might vary depending on a number of things. The following few sections will let you look at each one in detail.
1) Data scientist salary insights by location
Due to its emphasis on autonomous work and technology, the data science industry is well suited for working from home. A data scientist working from home earns an annual income of $153,137. Your income might still be impacted by your location or the location of your employer, though. The five US cities with the highest salaries for data scientists are shown below.
| Boston, MA | $170,758 per year |
| Los Angeles, CA | $165,887 per year |
| Houston, TX | $168,049 per year |
| Chicago, IL | $154,800 per year |
| Washington, DC | $147,169 per year |
2) Data scientist salary insights by industry
Your annual pay may be significantly influenced by the industry in which you work. For instance, real estate data scientists make 18% more money than their counterparts in other sectors. Information technology is the second-highest paid industry for data scientists (IT). IT data scientists make 14% higher money than workers in other sectors.
3) How education affects a data scientist's salary
51 percent, 34 percent, and 13 percent of data scientists hold master's degrees in addition to their bachelor's degrees (PhD). Typically, data scientists major in math, statistics, business, or engineering. The Burtch Works Pay Report for 2022 indicates that earnings for data scientists often rise as one's education level does.
4) How experience affects a data scientist's salary
Data scientists that have more experience often earn more money annually. When you advance from being a beginning data scientist (Level 1) to a mid-level data scientist (Level 2), and so forth, you may anticipate a rise in pay. Also, it's crucial to realize that professions requiring you to manage people pay more than those that do not. Average data scientist salaries are broken down by level of experience in the table below.
| Experience Level | Expected Salary |
| Data Scientist Level 1 | $90,000 |
| Data Scientist Level 2 | $115,000 |
| Data Scientist Level 3 | $145,000 |
| Data Scientist Manager Level 1 | $155,000 |
| Data Scientist Manager Level 2 | $200,000 |
| Data Scientist Manager Level 3 | $275,000 |
How To Increase Your Data Scientist Salary
As was already said, the more schooling you have, the higher your salary will be as a data scientist. Consider pursuing a bachelor's or master's degree in data science or a similar discipline if you don't already have one. A Doctorate may be necessary for some senior data scientist positions that pay more. Consider pursuing an advanced degree if you want to land a high-level position.
Building new skills as a data scientist
One of the methods to raise your wage is through getting a degree. By enhancing your skill set, you may also earn more money. Some of the most crucial technical competencies for data scientists to learn are listed in the list below:
- Machine learning/deep learning
- Artificial intelligence (AI)
- Risk analysis
- Cloud tools and data analysis platforms
- Software engineering skills/programming languages
- Statistical analysis
- Data mining and cleaning
- Big data
- Data warehousing and structures
Together with having the necessary technical knowledge and abilities, data scientists also need to be effective communicators. In order for non-data scientists to grasp their findings, they must be able to present them in an understandable manner. For individuals seeking a position in data science management, communication skills are particularly crucial. By obtaining an IBM credential in Data Analysis and Visualization, you may sharpen your data presentation and visualization abilities.
Enhancing your data scientist resume
The first step is to learn the aforementioned abilities. The next thing you must do is highlight these abilities in your CV. Earning a Professional Certificate in a pertinent field of expertise is one method to make sure your most in-demand abilities stand out to employers. Industry giants and recognised institutions like IBM, Microsoft, Stanford University, and the University of Colorado Boulder frequently provide professional certificates. Check out the following list of online programmes that, upon successful completion, award you with a degree in data science:
- Data Science Fundamentals with Python and SQL Specialization - IBM
- Business Intelligence Foundations with SQL, ETL, and Data Warehousing - IBM
- Microsoft Azure Data Scientist Associate (DP-100)
- Machine Learning Specialization - Stanford
- Data Science Foundations: Structures and Algorithms Specialization - University of Colorado Boulder
Common certifications
There is probably a relevant certification programme for you, whether you want to demonstrate your data analytics capabilities, obtain a certification from an accredited university, acquire more training as a new graduate, or enhance vendor-specific skills. For a profession in data science, the following certifications are frequently attained:
- Cloudera Certified Professional (CCP) Data Engineer
- Dell EMC Data Science Track (EMCDS)
- Google Professional Data Engineer Certification
- IBM Data Science Professional Certificate
- Microsoft Certified: Azure Data Scientist Associate
- Open Certified Data Scientist (Open CDS)
- SAS Certified Data Scientist
- Tensorflow Developer Certificate
Tools
Important decision-makers entrusted with analysing and managing vast volumes of structured and disorganized data are known as data scientists. Data scientists use a range of tools and programming languages to accomplish this, the most popular being SAS, Excel, Tableau, and Apache Spark.
Conclusion
It's important to note that the demand for data scientists continues to grow, with companies across various industries investing in data analysis and artificial intelligence. This high demand for skilled professionals can lead to competitive salaries and benefits packages. Therefore, it's possible that the data scientist salary in USA will continue to increase in the future, but it's also important to keep in mind that this could be influenced by various factors such as the state of the economy, industry trends, and competition.
