We are an university in the United States that develops online degree programs for adult students. The average age of our students is 35 years old. We will soon be launching a online master's degree in Data Science.
Data science has been called “the sexiest job of the 21st century” (see: https://hbr.org/2012/10/data-scient…-century/). Today’s employers need data professionals with the skills to turn big data into big insights and better business decisions. Data-science professionals work with computers to organize, analyze, and interpret large data sets in search of potential breakthroughs—new ways to solve problems and seize opportunities the organization never knew existed. Coding is a big part of their job, as is communicating discoveries through vibrant, high-tech-looking data visualizations. Data professionals are highly sought after by companies such as Google, Amazon, Microsoft, Walmart, eBay, LinkedIn, and Twitter. See below for helpful info from article.
What do data scientists look like?
Data-science professionals tend to skew male. They dress in professional or business-casual clothes and work closely with management and other business people. Model(s) should appear to be 35 to 40 years old.
Additional info from “sexiest jobs” article:
"More than anything, what data scientists do is make discoveries while swimming in data. It’s their preferred method of navigating the world around them. At ease in the digital realm, they are able to bring structure to large quantities of formless data and make analysis possible. They identify rich data sources, join them with other, potentially incomplete data sources, and clean the resulting set. In a competitive landscape where challenges keep changing and data never stop flowing, data scientists help decision makers shift from ad hoc analysis to an ongoing conversation with data . . . Often they are creative in displaying information visually and making the patterns they find clear and compelling."
The “data scientist” is a hybrid of statistician, data hacker, analyst, communicator, and trusted adviser.
Data scientists must communicate in language that all their stakeholders understand—and demonstrate special skills in storytelling with data, whether verbally, visually, or—ideally—both. Many data scientists working in business today were formally trained in computer science, math, statistics, economics or marketing. They can emerge from any field that has a strong data and computational focus.