Startups are producing so much data that they have become frantic to find more data scientists; salaries in the $300,000/year range are not unusual.
On Wednesday, June 11, at 11 a.m. PDT/2 p.m. EDT/7 p.m. GMT, @eWEEKnews will host its 21st eWEEKChat event. The topic will be "Defining the Role of Data Scientist: Hottest Job in IT." It will be moderated by Chris Preimesberger, who serves as eWEEK's
editor of features and analysis.
Some quick facts:
"Defining the Role of Data Scientist: Hottest Job in IT" Date/time:
June 11, 2014 @11a.m. PDT/2 p.m. EDT/7 p.m. GMT Hosted by: @eWeekNews Moderator:
Chris Preimesberger: @editingwhiz Tweetchat handle:
Use #eWeekChat to follow/participate in the chat Chatroom real-time links:
We recommend two: http://tweetchat.com/room/eweekchat
. These make it much easier to follow the conversation, comment or ask questions.
eWEEKchat Event news page: http://www.eweek.com/innovation/eweekchat-events/
Data science—the gathering and parsing of the enormous flood of data pouring into America's more technologically adept firms—is so hot that even President Barack Obama has declared it an educational priority. The Harvard Business Review has called data science "the sexiest job of the 21st century."
Companies in Silicon Valley are falling over themselves trying the find the best DS candidates. Startups are producing so much data that they have become frantic to find more data scientists; salaries in the $300,000/year range are not unusual.
Data scientists need a grounding in statistics and the basics of computer science, or a willingness to learn both. "Data scientists combine the analytical capabilities of a scientist or an engineer with the business acumen of the enterprise executive," SAP has declared.
A data scientist could function in a number of roles at an organization, depending upon how he or she is needed. Basically, however, a data scientist connects the dots between big data research/analysis and industry-specific knowledge and market trends and writes cogent reports on them in order to give his/her company a competitive advantage.
This person engineers systems that organize and funnel data through the most efficient company channels possible. Then, he/she translates the most valuable data into meaningful discussions, essentially breaking down technical stats and interactions into layperson language.
For example, the data scientist at Pinterest spends his time sifting through vast quantities of complicated data to find the underlying patterns. "Having found them, the only way I add value to the business is to get other people to see and understand those patterns," he said. "And the only way to do that is to present the data, either visually or in writing (or both) in the simplest way possible."
More and more colleges and universities are adding data science to their CS curriculums. Some of the questions we will pose on June 11 include:
Q1: Does your company currently employ a data scientist position/positions? How is the role used?
Q2: Is your company currently seeking a data scientist, and is it having difficulty finding good candidates?
Q3: Does your company currently make use of big data analytics, and if so, what type of employee is entrusted with finalizing reports and distributing them to stakeholders?
Q4: If your company already employs a data scientist, or a function similar to data scientist, what specific types of duties are they responsible for?
Q5: Does a data scientist position seem applicable only to midrange and larger enterprises, or could this also apply to SMBs?
Q6: What other strategic advantages do you see a data scientist bringing to an enterprise?
Join us today. You will come away learning something important.