Do You Really Need a Data Scientist?

The buzz in the big data world from 2012 is around the new position, Data Scientist.

But is this just hype—a new title for what is really a statistician or SQL power-user position?

Or is this a new way to approach big data—one that is critical to your success?

Below a 57’ conference try to response to the question:

http://bcove.me/0ahe6mmb

Tags: Big, Business, CRM, Data, Intelligence, Marketing, Media, Mining, Science, Social, More…Teradata, Warehouse

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Comment by Vincent Granville on February 15, 2013 at 10:23am

A data scientist is a bit of everything (statistician, software engineer, business analyst, computer scientist, six sigma, consultant, communicator), but most importantly she is a senior analytic practitioner

with a very good sense for business data and business optimization at large.
knowledge of big data - both drawbacks and potential (and able to leverage its potential)
who enjoys swimming in unstructured data, fuzzy non-SQL "joins"
who knows the limitation of old statistics (regression etc.) yet knows how to correctly do sampling, cross-validation, Monte Carlo simulations, design of experiments, assessing lift, identify good metrics
who knows the limitations of MapReduce, and how they can be overcome
who can design and develop robust, simple, efficient, reliable, scalable, useful predictive algorithms - whether or not based on statistical theory

A data scientist may not know much (but at least a little) about linear regression, statistical distributions, the complexity of the quicksort (sorting) algorithm or the limit theorems. Her knowledge of SQL can be a bit elementary, although she can run a big SQL query 10 times faster than business analysts who use tools such as Toad or Brio. Her strengths, skills and knowledge are briefly outlined above.

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