Organizations in industries across the world are shifting their strategies because of data. Take Google, Netflix or Amazon, for example. Each powerhouse organization has shot to the top of their space by adopting data analytics and data science into their very schema, an approach that others are now racing to replicate. With a data driven approach in mind, companies are looking to hire people to manage their data and uncover the value and meaning behind the information they are collecting. As such, data-driven career opportunities and careers in data analytics abound for people with data analysis skills.
While data analysts are highly sought-after, commanding salaries of $75,000 or more on average, learning data analytics can also open the door to other, equally lucrative, data-driven careers. (In fact, according to Gooroo, the average salary for jobs requiring data analysis skills in the United States is $85,000!) The six titles listed below are just a few of the many data-driven career pathways someone with skills in data analytics can take.
Business Analysts act as a bridge between the business problems an organization is facing, and the technology solutions that solve or mitigate them. BA training solutions described the job function best in their analogy: “being a business analyst is a bit like being an architect but instead of building a house, we are developing or updating a computer system.” Business analysts use data analytics to assess business models, understand and document requirements for technology integration, and share data-driven reports and recommendations with stakeholders. According to Glassdoor, the national average salary for a business analyst is just under $78,000.
An Information, or data architect, is similar to a business analyst in that both job functions require some level of process documentation. However, it is the information architect’s job is to organize and document the flow of content on a website based on user research, in order to provide an optimal structure. This could include anything from recommending how to order products on a page, to determining how to store metadata in a content management system. As information architecture is a component of user experience (UX) design, information architects not only need to know how to analyze data, but must also have strong visualization skills.
Data Scientists and data analysts are often thought of interchangeably. Sometimes even the experts have a hard time defining the difference! But, the two roles do carry different expectations (we’ve broken the respective job functions down here here). In short, data scientists predict the unknown by building predictive algorithms and models based on historical data. They are heavy duty coders and statistics experts who work with concepts and tools like data analysis, Machine Learning, hadoop, java, Python etc.
The U.S. Bureau of Labor Statistics has consistently ranked “Data Scientist” as the top job for the last 3 years. And they now predict that, “Job growth in the next decade is expected to outstrip growth during the previous decade, creating 11.5M jobs in the Data Science/Analytics area by 2026.”
Industry thought leader Mind the Product notes that more and more product management teams are “turning to predictive analytics as a source of competitive differentiation and additional value for end users.” In fact, in a recent survey of 500 product application teams, they found that predictive analytics is the number one feature that product managers are adding to their roadmaps.
As predictive analytics evolves to become a product standard, teams will need to hire product managers with both business and analytical skills to create competitive products that satisfy end-users.
Digital Marketing Manager
Marketing is one of the most competitive fields out there, where you often need to be “twice as good” as your fellow marketer. So how do you gain a completive edge? Currently, there is a massive shortage of marketers that are skilled in data analytics, as shown in the image provided by Vanngage below.
Venngage found that only 3% of all marketers are competent in analyzing large datasets at every level. They also uncovered that Excel and SQL skills have 3x and 5x more demand than supply, and that only 7% of marketing professionals have sufficient skills in Google Analytics. For marketers, learning analytics will open up more opportunities, as the BLS expresses that managers who can navigate the digital world will have an advantage when it comes to finding jobs.
Data engineers work very closely with data scientists and are responsible for developing the architecture that prepares data for analysis. In essence, a data engineer collects data, stores it and conducts batch processing so that they can then pass it on to a data scientist. Data engineering is one of the data science related careers expected to shape our future in 2019. And data engineers can typically rake in salaries exceeding $150,000.
Data is increasingly shaping the way we live and work, and there’s no sign of the trend slowing down. Data-driven careers are becoming the new norm. And with today’s disparity between demand and supply for analytics skills across industries and fields, there has never been a better time to learn data analytics and leverage it for your career advancement.