A person who is considering a degree in data science may wonder, “Does data science pay well?” The answer is important to know because a lot of students end up saddled with large loans that eat up a lot of their pay, making it difficult for them to save for retirement, buy a home or meet other personal goals they have for themselves. Being aware of the salary range for a data scientist could help a person decide if the typical pay would be in line with their financial situation upon graduation and well into their career.
Median Annual Wage for Data Scientists
According to the Bureau of Labor Statistics (BLS), the median annual wage for a data scientist was $118,370 in May 2018. This means that half of the people in the occupation earned less than that amount, and half earned more than that amount. The lowest-paid 10 percent earned around $69,230 and the highest-paid 10 percent earned an average of $183,820 per year.
Annual Salary for Data Scientists By Industry of Employment
Another way to decide whether or not data science pays well is by examining salaries for each industry that employs these professionals. The industry with the highest average annual pay for a data scientist is software publishing, with an average annual salary of $144,220. Data scientists who work in research and development earn the next-highest average annual salary, exceeding $122,000 per year. Excluding the postal service, the data scientists employed by the federal government earned an average of just over $109,000 per year. Local, state and private professional schools, colleges and universities paid data scientists an average of more than $82,000 per year.
Cities and States With the Highest Pay for Data Scientists
The cost of living varies a lot by metropolitan area and state. Within the same state, cities tend to have a higher cost of living than suburban and rural areas. When considering a salary offer, a data scientist should compare it against the cost of living for that area. According to the Bureau of Labor Statistics, the cities or metropolitan areas with the highest-paid data scientists in May 2018 were San Jose, Seattle, Huntsville, Palm Bay, Albuquerque, San Francisco, Boulder, Portland, New York, and Provo. The five highest-paying states were Washington, Alabama, Idaho, New Mexico, and California.
The Best Countries for Data Science Pay and Opportunity
While still listed at the top as of now, the US isn’t the only country in the world in which data science professionals are highly sought and can earn a solid wage. Just behind the US in terms of salary, demand, and overall opportunity for this type of worker is the United Kingdom. In the UK, data scientists are in high demand, and this is particularly true for those seasoned in artificial intelligence work.
Just behind the US and the UK are China, Canada, and India. These countries also pay well and need many data science pros to fill their growing needs in artificial intelligence, machine learning, and other, similar areas. From healthcare and manufacturing to research and IT development, these countries all hold a high value for the work of data science pros and will likely continue in that spirit for the foreseeable future.
Other Factors That Affect the Salary of Data Scientists
There are some other factors that go into the annual salary of a data scientist. Those who hold a master’s or doctorate degree may command a higher annual salary. With more years of experience, a data scientist will typically earn more. Those who publish articles in scientific journals may also earn more as a result of bringing in research funding. Data scientists who move into a supervisory or management role may also have higher than average annual salaries.
Individual Job Roles with the Best Data Science Pay
For those interested in the specific roles in data science that garner the best pay and most promising levels of demand, there are many that fit the bill. The following 10 career paths in data science represent some of the best available right now in these terms.
Data scientists work to locate, arrange, clean, and manage large batches of data for their employers. This role is similar to that of the data analyst but with a key exception of being much more technical in nature. These data experts must be able to sort often-confusing data sets and find and present patterns therein that are helpful to their employers’ purposes.
Machine Learning Engineer
As this job title suggests, today’s machine learning engineer is the expert who makes machines “learn.” By “learning”, these machines are essentially being programmed from scratch to operate in a specific desired manner. This job requires a strong mix of competencies in programming, statistics, software engineering, and numerous other key aptitudes.
Once software has been created and implemented in an organization, it still may require additional fine-tuning in order for it to work exactly as that organization needs. Enter the applications architect. These professionals are responsible for maintaining and often altering or creating new applications, interfaces, and infrastructures.
Enterprise architects work in much the same capacity as applications architects. These experts work to keep their organizations’ software and other computerized systems working just as needed. If the company makes a change and needs their software to change to reflect that change, these are the experts that get it done.
Data architects are the professionals who focus on data, its distribution, its use in databases, and more. They ensure the functionality of data systems and safe and effective access by those who should have access to it. System administrators and data analysts often rely significantly on the work of these experts.
The work of today’s infrastructure architect focuses on overseeing the overall computerized infrastructure of an organization. Are all systems functioning and working together as needed? Which IT components do which jobs? This professional answers these questions regularly while assuring the whole setup is working in tandem as their employer needs.
Data engineers perform batch and real-time data processing on previously-accumulated datasets. In addition, these experts create and maintain systems for that data to flow through and be stored in for access as it’s needed. The above-mentioned data scientist often relies greatly on the work of this professional.
Business Intelligence (BI) Developer
Business intelligence is defined as the combined aptitude of a business that’s based on strategy, technology, and proper data analysis. As such, the role of the BI developer is to oversee the cooperation of all of these elements. They also help to design networks of all of these elements so as to maximize their organizations’ business intelligence.
Statisticians are the experts who comb through large datasets in the effort to make sure businesses are as informed as possible and most capable of making good organizational decisions. Data sorting, grouping, analysis, and other skills must be applied for the worker to get this job done correctly. In addition, these professionals also often help to design and implement new data systems for their employers.
The Education Behind the Pay
While it can be easy to solely focus on what data science workers earn and the jobs they do to earn that pay, it’s also a good idea to be informed about how exactly they get there. Every data science worker achieves their position by first becoming properly educated in their particular field of expertise. As there are many specialties within the data science occupational field, there are also many diverse educational paths attributed to each of those focus areas.
Data scientists and some of the other roles listed above often achieve their positions through a degree in data science. This degree is likely to include some of the following courses:
- Mathematical Modeling
- Stochastic Methods for Data Analysis
- Image Processing and Computer Vision
- Advanced Python for Data Science
- Big Data Analytics
- Oracle Database Administration
- Advanced Machine Learning
For those seeking to get into data science work through the statistician approach, a degree in applied statistics is likely the most direct and appropriate educational pathway. Such a degree will likely include required coursework such as:
- Linear Algebra
- Theoretical Statistics
- Multivariate Analysis
- Experimental Design
- Statistical Methods
A computer science degree is yet another common route for getting into some of the top data science jobs such as those listed above. This degree typically includes courses such as:
- Theory of Computation
- Operating systems
- Numerical computation
- Compiler Design
- Real-Time Computing
- Distributed Systems
- Data Communication
In addition to degree programs being a reliable precursor to getting a good-paying job in data science, there are a number of certification programs many seek out in order to further their background skills and abilities in the field. The following are some of those certifications more frequently seen in these kinds of workers.
- Certified Analytics Professional (CAP)
- Cloudera Certified Associate (CCA) Data Analyst
- Cloudera Certified Professional (CCP) Data Engineer
- Data Science Council of America (DASCA) Senior Data Scientist (SDS)
- Data Science Council of America (DASCA) Principle Data Scientist (PDS)
- Dell EMC Data Science Track (EMCDS)
- Google Professional Data Engineer Certification
- IBM Data Science Professional Certificate
- Microsoft Certified: Azure AI Fundamentals
- Microsoft Certified: Azure Data Scientist Associate
- Open Certified Data Scientist (Open CDS)
- SAS Certified AI & Machine Learning Professional
- SAS Certified Big Data Professional
- SAS Certified Data Scientist
- Tensorflow Developer Certificate
Relevant Professional Associations
For those seeking further information on today’s growing field of data science jobs, there are a number of excellent resources with which further inquiry is recommended. The following organizations and agencies represent some of those authoritative resource points.
Data Science Council of America
The Data Science Council of America is a leading representative authority for the wide world of data science and its many workers. This organization researches and designs new components and systems in the data science field as well as acts as an accrediting body for schools and employers. At this time DASCA offers a total of six internationally recognized certifications that are highly valuable to the data science world and those looking to get into it. In addition, anyone can inquire with the organization and use many of its resources to learn more about all things data science.
Association for Information Science and Technology
The Association for Information Science and Technology, also commonly referred to as ASIS&T, is another very authoritative representative force across the world of data science. This is a non-profit membership association, but even without membership, anyone can utilize many of the group’s resources and inquire with them to learn about a great deal of subjects in data science. Among its many offerings are annual conferences and also regularly-produced publications such as the popular Journal of the Association for Information Science and Technology.
Association of Data Scientists
The Association of Data Scientists is yet another formally-recognized professional association for the field of data science and its many workers. The main mission of this group is to globally represent all workers in data science jobs as well as to help advance that very field simultaneously. Some of the resources available here include a regularly-published journal, ethics resources, training programs, and more. Membership with the organization offers even more excellent benefits.
Bureau of Labor Statistics
The Bureau of Labor Statistics is a great resource for learning about a wide array of jobs, job demand, industry pay rates, and more. While not a sole representative for data science itself, this US government agency does offer highly accurate info on this particular field of work along with many others. In addition, the BLS can be contacted directly for further inquiry into any desired info on today’s vast job market.
The median annual salary of a data scientist is something to keep in mind, especially if a person is considering earning an advanced degree and would need to take out additional loans in order to complete their education. The salary would also be important when examining an area’s cost of living or choosing a different type of housing arrangement. Knowing the answer to, “Does data science pay well?” could help a person work with a financial advisor and create a comfortable budget and reasonable financial goals.
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