Book - Data Scientists types and skills

This book describes Data Scientists types and most common skillsets, tells you why a complete Data Scientist probably doesn't exist.

MUST READ if you are creating a Data Science team.

The data scientists are classified as follows:

• Data Researcher
  The professionals in this category come from the academic world and have in-depth backgrounds in statistics or the physical or social sciences. This type of data scientist often holds a PhD but is weakly skilled in Machine learning, Programming or Business.

• Data Developer
  These guys tend to concentrate on technical issues that come with handling data. They are strong in programming and machine learning but weak in business and statistics skills.

• Data Creatives
  These are the guys who make something innovative out of mountains of data. They are strongly skilled in machine learning, Big Data, programming and other skills to handle massive data.

• Data Business people
  They represent the business side and are responsible for making vital business decisions through data analytics techniques.  They are an eclectic blend of business and technical proficiency.

Book Description:
"Despite the excitement around "data science," "big data," and "analytics," the ambiguity of these terms has led to poor communication between data scientists and organizations seeking their help. In this report, authors Harlan Harris, Sean Murphy, and Marck Vaisman examine their survey of several hundred data science practitioners in mid-2012, when they asked respondents how they viewed their skills, careers, and experiences with prospective employers. The results are striking.

Based on the survey data, the authors found that data scientists today can be clustered into four subgroups, each with a different mix of skillsets. Their purpose is to identify a new, more precise vocabulary for data science roles, teams, and career paths.

This report describes:

Four data scientist clusters: Data Businesspeople, Data Creatives, Data Developers, and Data Researchers
Cases in miscommunication between data scientists and organizations looking to hire
Why "T-shaped" data scientists have an advantage in breadth and depth of skills
How organizations can apply the survey results to identify, train, integrate, team up, and promote data scientists"

click to download:

sources:
http://cdn.oreillystatic.com/oreilly/radarreport/0636920029014/Analyzing_the_Analyzers.pdf
http://www.edureka.in/blog/types-of-data-scientists/?imm_mid=0bd168&cmp=em-strata-na-na-newsltr_20140528_elist