Do you have good mathematical, analytical, and programming skills and are wondering which career to opt for? Are you confused about which specialized area of data science you should work in? Or are you wondering what are some of the highest-paying data science jobs?
Data science is emerging as a rapidly growing field with the development of new technologies, increased commercialization, and the move toward a digital future. Organizations worldwide, from startups to multi-billion dollar companies like Google and Meta, are looking for experts in data science who can collect, analyze and process large volumes of data.
The insights data scientists derive from the trends in this data are of great value to companies, who then develop their business strategies and operational policies accordingly to achieve maximum growth and efficiency.
The popularity of data science can accurately be determined from the fact that the field is projected to grow by 31% from 2020 to 2030, which is 8% higher than the growth of other occupations during this period.
Data scientists not only have scope in terms of future job opportunities but also in terms of their salaries. The median annual wage of data scientists in 2022, as reported by the Bureau of Labor Statistics (BLS), is close to $101,000. Moreover, the best data scientist job can pay you an average of around $145,000, with those at the highest posts offering more than $200,000 annually.
So if you are looking to become a data scientist or are already on your way to becoming one, this blog lists 21 of the highest-paying data science jobs for 2023.
21 Highest Paying Data Science Jobs for 2023
Given the increasing demand for data science experts in today’s world, it is natural to wonder what their salaries might be. To assist you, we have drawn up a list of 21 of the highest-paying jobs in data science that you can choose from if you are interested in pursuing a career in this field:
1. Data Scientist (National Average Salary Per Year: $144,975)
Salary range: $58,000 to $100,421
Data scientists process and analyze large amounts of structured and unstructured data. They determine patterns in this data and provide organizations with insights that help them grow and become more efficient.
2. Big Data Engineer (National Average Salary Per Year: $137,751)
Salary range: $85,900 to 220,870
The role of big data engineers is to process large amounts of complex data, find and collect answers to the questions posed by the information in this data, and run large-scale processing systems and databases in organizations.
3. Enterprise Architect (National Average Salary Per Year: $136,937)
Salary range: $96,600 to $192,000
Enterprise architects help companies reduce costs and ensure efficiency by determining which technology systems can effectively help them implement their business strategies. Enterprise architects work in the IT department of organizations
4. Machine Learning Engineer (National Average Salary Per Year: $125,390)
Salary range: $64,000 and $246,000
Machine learning engineers aim to understand how machines can function on their own through the use of Artificial Intelligence (AI). Through their expertise in machine learning, mathematics, and programming, they develop different types of algorithms for smartphones, online websites, etc.
5. Principal Statistical Programmer (National Average Salary Per Year: $118,360)
Salary range: $101,000 to $232,000
Principal statistical programmers collect and analyze data from clinical trials through Statistical Analysis Software (SAS programs) and work to enhance clinical programming processes. Their job is also to ensure that the data they gather is accurate, high-quality, and meets industry requirements.
6. Data Architect (National Average Salary Per Year: $118,264)
Salary range: $105,000 to $250,000
Data architects work in the IT departments of various industries to work on the infrastructure and frameworks of database systems. In other words, they determine the best technologies, tools, and policies to collect a certain type of dataset while ensuring it remains secure.
7. Infrastructure Engineer (National Average Salary Per Year: $117,692)
Salary range: $62,775 to $220,650
Infrastructure engineers work in the Information Technology department of companies to ensure that all technological systems run smoothly and efficiently. They help employees solve technical issues that they may be facing by identifying problems and troubleshooting their systems.
8. Clinical Statistical Programmer (National Average Salary Per Year: $103,724)
Salary range: $84,000 to $191,000
Clinical statistical programmers structure and analyze data during clinical research and trials using Statistical Analysis Software (SAS programs). Their responsibility also includes auditing data and ensuring that it is delivered at the right time, with accuracy and high quality.
9. Data Modeler (National Average Salary Per Year: $103,164)
Salary range: $77,520 to $137,200.
Data modelers work with data architects and administrators to structure raw data comprehensively and develop physical or conceptual data models to ensure efficiency.
10. Database Developer (National Average Salary Per Year: 98,961)
Salary range: $67,200 to $ 145,700
Database developers are programming experts responsible for managing databases and developing ways to store company data and make it accessible when necessary.
11. Data Warehouse Manager (National Average Salary Per Year: $97,717)
Salary range: $63,100 to $151,330
Data warehouse managers are senior-level experts who oversee a team of engineers’ work in designing and maintaining data warehouse systems and the information flow in and out of these systems.
12. Modeling Analyst (National Average Salary Per Year: $97,035)
Salary range: $62,456 to $150760
Modeling analysts organize data and visually represent the information gathered from complex data sets in graphs and diagrams. Moreover, they also assist in tasks such as data mining and database management.
13. Modeling and Simulation Analyst (National Average Salary Per Year: $97,035)
Salary range: $97,035 to $150,760
Modeling and simulation analysts model and analyze data through their computer programming skills. Their job is to try and predict outcomes through simulations, analyze them and determine which solutions would work for them.
14. Clinical Programmer (National Average Salary Per Year: $95,974)
Salary range: $66,000 to $165,000
Clinical programmers use SAS programs and develop algorithms to maintain and analyze clinical data, i.e. data from clinical trials. They then compile all this data from their research and check it for accuracy and quality.
15. Database Administrator (National Average Salary Per Year: $90,549)
Salary range: $61,380 to $133,600
Database administrators (DBA) work in different industries’ Information Technology (IT) departments. Their primary job is to manage the database where complex data sets are collected and ensure that employees can access these databases safely.
16. Decision Science Analyst (National Average Salary Per Year: $89,845)
Salary range: $65,000 to $148,000
Decision science analysts are math experts who work with statistical data, structure it, analyze it, and provide companies with factual insights to help them make decisions. Decision science analysts are also responsible for conducting audits, determining project feasibility, and working out cost allocations.
17. Statistical Programmer (National Average Salary Per Year: $89,291)
Salary range: $66,000 to $142,000
Statistical programmers play a key role in understanding research from clinical trials, analyzing their data, and providing useful insights that they can represent in graphs, tables, and diagrams. In addition, statistical programmers also help ensure quality control, security, and accuracy of the data.
18. Statistician (National Average Salary Per Year: $88,995)
Salary range: $57,230 to $138,230
Statisticians collect data from multiple sources, organize it, ensure its accuracy, and analyze it to determine various trends and patterns. They then study these trends carefully, use statistical models, and verify conclusions that may be necessary for growth and efficiency
19. BioMetrician (National Average Salary Per Year: $79,162)
Salary range: $59,000 to $180,000
Biometricians use their mathematical abilities to help make informed decisions in health care. Their job is to analyze data from clinical trials, pharmaceutical factories, and medical programs and understand the advantages and disadvantages of their projects and how they can be modified to ensure efficiency.
20. Business Intelligence Analyst (National Average Salary Per Year: $78,787)
Salary range: $54,100 to $114,730
Business intelligence analysts work specifically to help businesses develop and implement market strategies that can help them grow and become efficient. To achieve this, business intelligence analysts collect and analyze data that enables them to understand various products, current market trends, and user behaviors through the use of multiple tools and techniques that provide accurate insights.
21. Data Miner (National Average Salary Per Year: 53,440)
Salary range: $36,000 to $94,000
Data miners’ responsibility in the field is to use various tools and techniques to clean and model data. They filter out irrelevant information in the raw data and help companies determine patterns that occur in this data to help companies make decisions accordingly.
Conclusion
Data scientists are in demand because of the role they play in helping companies develop their businesses, understand user behavior and eventually grow. The Bureau of Labor Statistics projects that in the ten years between 2020 and 2030, data science jobs will rise by 31%, which shows the scope for data scientists now and in the future.
In this article, we’ve discussed 21 of the highest-paying data science jobs to give you an idea of the scope of this field. The average annual salary you can expect to earn from jobs in the data science field is almost $101,00. Experts in senior-most positions can expect to earn higher than $200,000 a year.
If you are looking to enter the data science field and do not have a degree or past experience, you must attend data science bootcamps, enroll in diploma courses, earn certifications, and intern with organizations to develop your skills. In addition, you must gain in-depth knowledge of machine learning and big data, a collection of large volumes of data that increase exponentially. Lastly, building a strong portfolio and resume and sharing your work with potential employers is wise.
FAQs
Data scientists help organizations process and analyze large volumes of structured and unstructured data and determine trends and patterns in the information that they collect. The insights that they provide are used by these organizations to develop their policies, and business strategies and to learn more about their customers and audience.
Data science is a vast field and data scientists earn different salaries depending on their area of specialization, their experience, expertise, and the place where they are working. Still, on average, the median annual salary for data scientists as reported by BLS is almost $101,000 with the lowest positions paying around $40,000 to $50,000 and the senior-most posts paying $200,000 and above.
Data science is a field that requires excellence in mathematics, data analytics, programming, machine learning, and handling big data, among many other skills. While most jobs require at least a Bachelor’s degree in a relevant field, you can get a data science job without a degree by enrolling in bootcamps and diploma courses, doing internships, earning certifications, and applying for entry-level data science positions.
Data science positions are highly competitive so if you want to land a job in data science and have no prior experience, you will need rigorous practice in skills like programming, handling big data, and machine learning so that you can become eligible to apply for the job. On top of that, you will need to build a portfolio of your work, share it with potential employers and write a strong resume.
Big data is a collection of complex data sets that keep increasing in volume, variety, and velocity. The information that big data carries is so vast that it cannot be managed by regular computing systems and requires a variety of methods, tools, and technology to process. If organized and analyzed successfully, big data plays a crucial role in helping companies understand consumer behavior and market trends and develop strong business strategies.
Most companies require at least a Bachelor’s degree in data science, computer science, or a similar field for roles in big data engineering. Individuals with relevant Master’s degree land jobs in higher positions. While a degree will definitely make the process of getting a job easier for you, you can apply for entry-level positions without a degree if you have the skills that it takes to work in big data.
