Data science enables retailers to influence our purchasing habits, but the importance of gathering data extends much further.

Data science can improve public health through wearable trackers that motivate individuals to adopt healthier habits and can alert people to potentially critical health issues. Data can also improve diagnostic accuracy, accelerate finding cures for specific diseases, or even stop the spread of a virus. When the Ebola virus outbreak hit West Africa in 2014, scientists were able to track the spread of the disease and predict the areas most vulnerable to the illness. This data helped health officials get in front of the outbreak and prevent it from becoming a worldwide epidemic.

Data science has critical applications across most industries. For example, data is used by farmers for efficient food growth and delivery, by food suppliers to cut down on food waste, and by nonprofit organizations to boost fundraising efforts and predict funding needs.

In a 2015 speech, Economist and Freakonomics author Steven Levitt said that CEOs know they are missing out on the importance of Big Data, but they do not have the right teams in place to perform the skills. He says, “I really do believe still that the combination of collaborations with firms’ big data and randomization […] is absolutely going to be at the center of what economics is and what other social sciences are going forward.”

Pursuing a career in data science is a smart move, not just because it is trendy and pays well, but because data very well may be the pivot point on which the entire economy turns.

In-Demand Data Science Careers

Data science experts are needed in virtually every job sector—not just in technology. In fact, the five biggest tech companies—Google, Amazon, Apple, Microsoft, and Facebook—only employ one half of one percent of U.S. employees. However—in order to break into these high-paying, in-demand roles—an advanced education is generally required.

“Data scientists are highly educated–88 percent have at least a master’s degree and 46 percent have PhDs–and while there are notable exceptions, a very strong educational background is usually required to develop the depth of knowledge necessary to be a data scientist,” reports KDnuggets, a leading site on Big Data.

Here are some of the leading data science careers you can break into with an advanced degree.

Business Intelligence (BI) Developer

Average Salary: $89,333

Typical Job Requirements: BI developers design and develop strategies to assist business users in quickly finding the information they need to make better business decisions. Extremely data-savvy, they use BI tools or develop custom BI analytic applications to facilitate the end-users’ understanding of their systems

Notable Companies: DollarShave Club, Discover, and Liberty Mutual

Data Architect

Average Salary: $137,630

Typical Job Requirements: Ensure data solutions are built for performance and design analytics applications for multiple platforms.

Notable Companies: IBM, eBay, AAA Club Alliance, T-Mobile

Applications Architect

Average Salary: $134,520

Typical Job Requirements: Track the behavior of applications used within a business and how they interact with each other and with users.

Notable Companies: UPS, Humana, Dow Jones, Oracle

Infrastructure Architect

Average Salary: $126,353

Typical Job Requirements: Oversee that all business systems are working at optimally and can support the development of new technologies and system requirements. A similar job title is Cloud Infrastructure Architect, which oversees a company’s cloud computing strategy.

Notable Companies: Abbott Labs, Hewlett-Packard, Dell, Ford Motor Company

Enterprise Architect

Average Salary: $161,272

Typical Job Requirements: According to Techopedia, an enterprise architect, “Works closely with stakeholders, including management and subject matter experts (SME), to develop a view of an organization’s strategy, information, processes and IT assets.”

Notable Companies: Cisco, Boeing, Lockheed Martin, Microsoft

Data Scientist

Average Salary: $139,840

Typical Job Requirements: Find, clean, and organize data for companies. Data scientists will need to be able to analyze large amounts of complex raw and processed information to find patterns that will benefit an organization and help drive strategic business decisions. Compared to data analysts, data scientists are much more technical.

Notable Companies: Facebook, Capital One, Airbnb, Twitter

Data Analyst

Average Salary: $83,878

Typical Job Requirements: Transform and manipulate large data sets to suit the desired analysis for companies. For many companies, this role can also include tracking web analytics and analyzing A/B testing.

Notable Companies: Walmart, Gap, Bank of America, Kohler

Data Engineer

Average Salary: $151,307

Typical Job Requirements: Perform batch processing or real-time processing on gathered and stored data. Make data readable for data scientists.

Notable Companies: Spotify, Verizon, General Motors, Shutterfly

Machine Learning Scientist

Average Salary: $139,840

Typical Job Requirements: Research new data approaches and algorithms.

Notable Companies: Apple, The Johns Hopkins Hospital, Expedia, Tinder

Machine Learning Engineer

Average Salary: $114,826

Typical Job Requirements: Create data funnels and deliver software solutions.

Notable Companies: Nike, Dropbox, LinkedIn, Uber

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