What the industry calls a 'data scientist' now is really several different roles.. each requiring a different skill set.
1 business analyst
The role of business analyst existed long before the terms "big data" or "data scientist" were in vogue. This person works with front-end tools, meaning those closest to the organization's core business or function, such as Microsoft Excel, Tableau Software's visualization tools, or QlikTech's QlikView BI apps. A business analyst might also have sufficient programming skills to code up dashboards, and have some familiarity with SQL and NoSQL.
2 machine learning expert
The second data science role is that of machine-learning expert, a statistics-minded person who builds data models and makes sure the information they provide is accurate, easy to understand, and unbiased.
"These are the people who develop algorithms and crunch numbers," said Wu. "They are interested in building models that predict something."
3 data engineer.
The third key job, data engineer, is "the bottom layer, the foundation," said Wu. "They are the ones who play with Hadoop, MapReduce, HBase, Cassandra. These are people interested in capturing, storing, and processing this data… so that the algorithm people can build models and derive insights from it."
Read more at Information Week
