10 Best-Paying Jobs in Data Science
Looking for a career in data science, machine learning, artificial intelligence, or data architecture? Here are the roles with the highest salaries.
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For many years, data science has been one of the hottest -- and highest-paying -- fields in IT, and that trend continues in 2022. At the time of writing, job board Indeed.com had 44,871 jobs listed that included the phrase “data science,” and a similar LinkedIn search matched 321,416 postings in the US.
It’s worth noting, however, that not all these postings are for jobs where the specific title is “data scientist.” Today, a growing number of highly varied positions require some data science skills. Companies are looking for developers, product managers, IT managers, business analysts, writers, consultants, interns, and even marketing professionals with some data science capabilities.
In addition, many companies now have entire data science departments with defined career ladders. Some firms have directors and vice presidents of data science, and there is even a very, very small group of C-level executives with “chief data scientist” title.
Much of the reason for this increase in demand is the number of companies that are investing heavily in analytics, artificial intelligence (AI), and machine learning (ML). According to IDC, the market for big data and analytics tools topped $215 billion in 2021 and will grow at 12.8% per year through 2025. And Gartner forecasts that 2022 revenues from AI software will total $62.5 billion this year.
These sorts of investments are driving up demand on two different fronts: technology companies need workers with data science skills to help them create these products; and the enterprises buying the software need workers with data science skills to help them use it.
This increase in demand is coming at a time when IT managers were already having a hard time filling available positions. A survey conducted by Robert Half Technology found that “94% of technology team leaders said it’s difficult to find skilled technology professionals, with the most challenging areas being data science and database administration; business intelligence, analysis and reporting; and cloud architecture and operations.”
In order to attract talent, companies have been raising salaries, and the increases for data science jobs are among the most significant. The following slides highlight the 10 best-paying data science roles for 2022, based on averaged numbers from Robert Half Technology, Indeed, Glassdoor, and Payscale.
Average pay: $100,000 – $110,000
Data modelers provide a bridge between business functions and the data science team. As the name suggests, they are responsible for designing the data models used for analytics. They either need a deep understanding of the relevant business area or excellent research skills that allow them to untangle the complex relationships among an organization’s various data sources and repositories. The position also requires knowledge of fundamental data science principles, although it may not require the advanced math skills of other data science jobs.
To qualify for a data modeling job, you usually need at least a bachelor's degree and sometimes a master's degree. You'll also need at least five years of experience working in a data management or analytics capacity and experience with data modeling tools.
Average pay: $120,000 – $125,000
Machine learning (ML) engineers are computer programmers with advanced knowledge of ML techniques. They create algorithms, as well as designing and training ML models for a variety of purposes, such as business data analytics, image processing, language processing, recommendation engines, risk analysis, and more. Their responsibilities are often very similar to those of a data scientist, but they typically have a computer science background while data scientists have often studied more advanced mathematics.
To become a machine learning engineer, you will need at least a bachelor's degree in computer science or engineering, while some jobs require a more advanced degree. You will also need some training and/or experience in machine learning.
Average pay: $120,000 – $125,000
A data warehouse manager oversees the daily activities of the team responsible for working on data warehouse systems. They ensure that these systems are properly designed, implemented, and maintained in a way that is efficient, cost-effective, and secure. In addition, they are responsible for recruiting, hiring, and training new employees. The team they manage often includes data architects, data engineers, software engineers, and data analysts, so they must possess sufficient knowledge of these different fields.
Typically, data warehouse managers are required to have a bachelor’s degree and at least five years of experience working on data warehouse systems or something similar. Some positions may also require a master’s degree and/or one to three years of supervising experience.
Average pay: $120,000 – $130,000
Data scientists use data analysis and data processing to provide an organization with meaningful insights on how to improve their business. They collect vast amounts of data, design algorithms to process the data, organize and clean the data to ensure accuracy, identify useful patterns and trends in the data using analytics, and communicate their findings to the company through visualizations and reports. Data scientists generally have a wide array of different skills -- especially in advanced mathematics and statistical analysis, but also in programming and machine learning.
All data scientist positions require a bachelor’s degree at the minimum. However, most data scientists also have a more advanced degree in mathematics, statistics, computer science, or some related field, and many positions may require a master’s or a doctorate.
Average pay: $130,000 – $140,000
Big data engineers build and maintain the infrastructure that organizations use to store and process large quantities of information. This is important because the systems that big data engineers construct, transform raw data into a form that can be used by data scientists. Big data engineers are typically skilled software developers whose responsibilities include creating ETL systems, wrangling data from disparate sources, maintaining data warehouse systems, optimizing data quality, and building algorithms for data science teams.
Big data engineers are required to have a bachelor’s degree in computer science, software engineering, or a related field. They are also expected to possess knowledge of several different programming languages and data management systems and to have three to five years of experience in either software development or data management.
Average pay: $140,000 – $150,000
A data science manager is in charge of a data science team that works together to analyze data in order to improve business decisions. They manage the daily activities of their employees and ensure that every project runs smoothly from beginning to end. They are responsible for hiring and mentoring other data scientists, determining specific projects for their team, partnering with other departments to turn insights into solutions for the company, and implementing new technologies and concepts among the data science team.
To qualify for a data science management position, you must have a bachelor’s degree, at least five years of prior experience working as a data scientist, and usually a master’s degree in a related field. In some cases, supervisory experience may also be required.
Average pay: $140,000 – $155,000
A data architect is an IT professional whose job is to analyze data infrastructure and design the databases that are used for collecting and interpreting big data. They provide the blueprints that the data engineers use to build data management systems. Among other things, data architects analyze and plan a data architecture framework, recommend solutions to improve existing systems, and collaborate with programmers and data engineers to make sure their designs are implemented effectively.
To become a data architect, you need a bachelor’s degree in an IT-related field as well as five years of IT experience. Many employers also prefer that you have some previous experience working in data science.
Average pay: $150,000 — $160,000
Artificial intelligence (AI) architects are similar to data architects, but they specifically focus on designing AI models and implementing AI into existing data systems. AI architects are generally skilled software developers with experience working with artificial intelligence.
In order to become an AI architect, you need a bachelor’s degree in data science or an IT-related field and in most cases a more advanced degree as well. You also need five to 10 years of relevant work experience and experience with AI and machine learning.
Average pay: $170,000 – $180,000
A data science director is a high-level data scientist who determines the general strategies and goals of a company’s data science department. A person who becomes a data science director will have a similar role to a data science manager, but they will be less involved with the day-to-day activities of the data science team and may have data science managers working below them. They will be responsible for the department’s policies, budgets, long-term goals, and for recommending specific business decisions to business leaders.
To become a data science director, you must have five to 10 years of data science experience and at least five years of managerial experience. You should also be familiar with different procedures and technologies within data science department, as well as the company as a whole.
Average pay: $190,000 — $200,000
Vice president of data science is an advanced-level data science position that only exists in large companies. Usually, the vice president of a data science department will do little technical work and will focus mainly on determining strategic objectives of the data science function, managing lower-level managers, and engaging with business leaders. They should have strong leadership and interpersonal skills as well as expertise in both data science and business administration.
To qualify for this position, you must have 10 to 20 years of experience in data science as well as five to 10 years of managerial experience. Some companies may also require an advanced degree in business or a data science related field.
Average pay: $190,000 — $200,000
Vice president of data science is an advanced-level data science position that only exists in large companies. Usually, the vice president of a data science department will do little technical work and will focus mainly on determining strategic objectives of the data science function, managing lower-level managers, and engaging with business leaders. They should have strong leadership and interpersonal skills as well as expertise in both data science and business administration.
To qualify for this position, you must have 10 to 20 years of experience in data science as well as five to 10 years of managerial experience. Some companies may also require an advanced degree in business or a data science related field.
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