Data Professionals Are in High Demand—Here Are 8 Jobs You Should Consider was originally published on The Muse, a great place to research companies and careers. Click here to search for great jobs and companies near you.
Are you looking for a career with a significant amount of potential and opportunity in 2021 (and beyond)? If so, one career path you’ll definitely want to explore is data and analytics.
According to the World Economic Forum’s The Future of Jobs Report 2020, the top three jobs with increasing demand across industries in the United States—data analysts and scientists, AI and machine learning specialists, and big data specialists—all fall under the data and analytics umbrella.
“This is a rapidly growing field,” says Mark Herschberg, a CTO with experience running data analytics and data science teams, an instructor at MIT, and the author of The Career Toolkit: Essential Skills For Success No One Taught You. “As companies move online, we are awash in data. The growth of [internet-of-things] devices and digital interfaces to everything generates massive volumes of data which companies want to analyze and understand for optimization and advantage.”
Data and analytics can also help you get your foot in the door at a variety of companies and industries (for example, according to the WEF report, more than 80% of companies are likely to adopt big data analytics technologies by 2025). And having a background in data and analytics can help you find jobs in different departments within those companies or industries. “For example, marketing in the twentieth century was dominated by Don Draper and his sales pitch; today it’s dominated by quants with spreadsheets,” Herschberg says.
Clearly, data and analytics is a hot field that’s worth checking out. But what, exactly, are the roles you may want to consider? Here are eight possibilities (along with salary information from the compensation resource Payscale, whose database is updated nightly; the figures below reflect the latest information as of January 2021):
Average salary: $61,071
Salary range: $44,000–$86,000
Data analysts are responsible for gathering and organizing large sets of data—and then, as the name implies, analyzing that data and using their analysis to draw specific business conclusions, whether that’s how to effectively price products, cut costs, or improve customer retention. Data analysts also are in charge of managing all things data-related, including reporting, data analysis, and the accuracy of incoming data.
Data analytics typically need a bachelor’s degree in an analytics-related field, like math, statistics, finance, or computer science. Alternatively, there are also boot camp–style courses in data analysis that can help candidates get their foot in the door.
Average salary: $96,208
Salary range: $67,000–$134,000
While a data analyst’s main responsibility is to examine and analyze data, a data scientist’s main function is to create the framework for that analysis to happen. This includes implementing statistical models and algorithms, running data testing and experiments, developing data products, and continually optimizing their frameworks to better analyze the data—all with an eye toward reaching the most accurate business conclusions.
A bachelor’s degree in computer science, math, statistics, engineering, or a related field is typically required to land a role as a data scientist—although many companies prefer candidates with advanced degrees.
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Average salary: $112,374
Salary range: $76,000–$154,000
Machine learning engineers are programmers who create the algorithms, models, systems, and frameworks that allow machines to effectively learn and perform functions independently—no commands required. Machine learning engineers also are responsible for transforming models created by data scientists into real code that can be used in production.
Machine learning engineers should be fluent in programming languages (including Java and Python) and have a bachelor’s or advanced degree in computer science, math, statistics, or a related field.
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Average salary: $69,163
Salary range: $51,000–$95,000
Business intelligence analysts are focused on using data to improve an organization. This may include gathering, organizing, and analyzing both internal and external industry data—and then using that data to identify trends, patterns, or potential issues that need to be addressed. Business intelligence analysts are also expected to translate their data analysis into actionable strategies to improve the business—and present their strategic analysis to leadership.
This is a highly technical role—and, as such, candidates typically have a bachelor’s degree in computer science, math, or a related field. Many business intelligence analysts also pursue advanced degrees, including MBAs—and some companies may require an advanced degree.
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Average salary: $58,455
Salary range: $44,000–$83,000
Logistics analysts are responsible for using data to optimize supply chain processes, from procurement to shipment to delivery. Logistics analysts use data to identify potential profit loss within the supply chain—and then leverage that data to develop cost-saving solutions to make the production, distribution, and delivery of products more efficient.
Logistics analysts typically have a bachelor’s degree—but a proven track record in logistics and supply chain management can be enough for qualified candidates to get their foot in the door.
Average salary: $119,249
Salary range: $77,000–$156,000
Just as an architect designs physical structures, a data architect designs the structures an organization needs to effectively acquire, organize, analyze, manage, and utilize data. This includes translating business objectives into a data management framework, designing the framework, defining how data will flow through the framework, and working with other teams and engineers to develop the framework and implement it across the organization.
Most data architects hold a bachelor’s degree in computer science or computer engineering—though many also hold advanced degrees.
Average salary: $69,635
Salary range: $51,000–$98,000
As the name suggests, business systems analysts are responsible for analyzing and leveraging data to improve an organization’s systems and processes—particularly within information technology (IT). They use data tools to analyze the company’s current systems—and then identify ways to optimize systems, cut costs, and make IT more effective across the organization. Business systems analysts may also research new systems and tools to improve IT—and then assist in rolling out those systems across departments.
Business systems analysts generally have a bachelor’s degree in a tech-related field like information technology management or information systems. However, candidates with a business background and a strong interest in and knowledge of IT could also be a good fit.
Average salary: $56,436
Salary range: $41,000–$78,000
Marketing analysts are responsible for helping companies better understand their customers and market. Generally, marketing analysts analyze data sets related to a company’s target demographic (including market research, purchasing trends, and customer surveys)—and use their analysis to develop strategies to help companies better connect with new customers and more effectively market to their existing customer base. Marketing analysts also need to present their findings to leadership as well as colleagues in marketing and other non-technical departments—so they need to have the ability to translate their analysis into reports, charts, and other materials that are easy to understand and act on.
Marketing analysts typically have a bachelor’s degree and can come from a variety of educational backgrounds, including marketing, economics, business, math, statistics, or psychology.
Clearly, there are opportunities galore in data and analytics. But the question is, are these roles right for you?
According to Herschberg, there are a few things you need to succeed in the data and analytics fields—starting with strong quantitative and analytical skills. “You need left-brained analytical skills to do the analysis, which ranges from basic statistics to complex machine learning algorithms,” Herschberg says. “It’s not just knowledge of the tools, but knowing when to use each tool.”
Being numbers-driven is a must to succeed in data and analytics—but so is being able to explain those numbers to people whose knowledge of data and analytics ranges from expert to novice. “To be really successful you should also have the ability to explain complex technical ideas, concepts, and learnings” to folks in non-technical roles, Herschberg says.
Finally, data can be a force for good—or, if it’s misused, it can be just the opposite. So, Herschberg says, you need to “understand the limits of data, how it can be misused, and the ethical issues stemming from data analysis.”
Data and analytics is a field brimming with opportunity and future growth. And with this list, you have the jumping off point to start exploring roles under the data and analytics umbrella—and find one that feels right for you. So what are you waiting for? Get out there and get searching!