The Defining Job for Big Data - Data Scientist

The U.S. Bureau of Labor Statistics predicts that there will be a 24 percent increase in demand for professionals with management analysis skills over the next eight years. The need for this specialized talent is being fueled by the emergence of Big Data. 

As organizations increase the use of business analytics to better understand the data generated online, via social networks and mobile devices, or through real time sensors, they are under pressure to have infrastructure and skills to understand, measure, act and even predict outcomes based on so much data, of variety types and coming at explosive speed. 


These skills cannot rise straight from the rank-and-file IT staffs who have technical skills around Hadoop, MapReduce or Cassandra, nor would it be fully reside within the expertise of staff statisticians or analysts. The complexity of dealing with such a vast data set and connecting it to business value and foresight demand a new breed of skils, in what some have called data scientists. 

A data scientist is someone who can leverage modern computing infrastructure, platform and software to analyze large volume of diverse and fast-changing data sets, in order to uncover knowledge, predict outcome and prescribe solution. In short, a data scientist is the master of Big Data analytics.  

Here are some notable quotes I found around this topic: 

"As data of all shapes and sizes swell at record speeds the need will continue to grow for those individuals with an advanced understanding of how to interpret and respond to this information."   - Deepak Advani, IBM vice president of predictive analytics

“Business leaders are faced with an enormous, and ever-increasing, amount of complexity. It is critical that we prepare the next generation of leaders with the skills to find trends and patterns in this vast amount of data. The field of analytics provides powerful tools to find meaning and opportunity amid complexity.”   - Julio M. Ottino, Ph.D., dean of the McCormick School of Engineering at Northwestern University 

"Job descriptions for data scientists are starting to gel. While statistical and mathematical skills form a core part, creative thinking about how Big Data can improve aspects of the business, such as new operating policies or customer engagement models, is equally important for success. Data scientists should have an aptitude not only for hard programming skills in SAS, SPSS, and R, but also for understanding how to display or visualize information in a business context. Data science is therefore a business practice, rather than a defined set of statistical or technology competencies." - Madan Sheina of OVUM

And some more publications: 

• Competing on Talent Analytics by Harvard Business Review (online)