A data scientist at Flutura has to wear multiple hats in order to deliver next generation analytical solutions in the sectors we operate in namely energy, telecom, digital and health care industry. In order to do that he/she has to **wear 3 hats**

- The **BUSINESS** hat

- The **MATH** hat

- The **DATA** hat

Most of the time it’s easy to fathom the depth of the data scientists math / algorithmic knowledge and the depth of his/her understanding on handling high velocity data and unstructured data points. But one area of weakness is the business dimension. ** So how do you decide whether a data scientist can be put in front of the business?** This blog talks about

Human Beings are **wired more to listen to stories than to read numbers**. Flutura data scientists were doing data forensics on mobile app funnel drop analysis for an online travel agency was able distil the quintessential essence of all essences - *That the mobile user who was getting dropped was a 20 something, last minute booker travelling between metros and trying to complete the transaction from a Samsung mobile using Android os and the friction point was the payment gateway*

Therefore

- Can the data scientist translate numbers into stories? This is a very important tool to build bridges with business. Else a data scientist has the risk of getting struck in the world of math and unable to make the connect.

Other 7 tests are elaborated at

http://blog.fluturasolutions.com/2012/12/8-tests-to-decode-business...

So in a nutshell here are 8 questions to ask

- “RESONANT STORY TELLING” TEST

- Can the data scientist
**narrate**a compelling and**resonant story**from the data patterns?

- “STRING OF PEARLS” TEST

- Can the data scientist
**connect the dots**and form a “necklace” from the pearls of insights discovered from cryptic log file data points?

- “NEEDLE MOVEMENT” TEST

- Which are the
**best “impact zones”**for use cases which are “ripe” for big data?

- “SNIFF THE DOMAIN OUT” TEST

- Can the data scientist
**“sniff the domain out”**by examining analytical outputs and getting the business to put the numbers in context?

- “ACTIONABILITY” TEST

- What was the data scientist’s role in
**operationalizing actions**or did his prior engagements end with**recommendations**?

- “USE CASE CURATION” TEST

- Can we give a raw data set and can the data scientist take 3-5 minutes to
**curate an interesting possibility**from the raw data set ?

- THE “NORTH POLE” TEST

- Can the data scientist work with business to articulate the ‘as is’ state and the expected
**‘to be’ state**of the decision making process after the analytical solution is implemented?

- THE “WHAT DO YOU SEE” test

- Can the data scientist construct
**3-4 meaningful English statements**from clustering outputs, keyword frequencies, Box plots and other analytical outputs?

These tests are by no way collectively exhaustive or perfect. But it serves as a reasonable starting point to get the right DNA of Data Scientists into the organisation. Else we run the risk of having people who just knows how to create a Hadoop cluster :) as being labelled a data scientist.

As the saying goes “The real voyage of discovery consists not in seeking new landscapes but in having new eyes.”- Marcel Proust

Good luck with your efforts to recruit the rare species – the holistic data scientist :) !!!

Other 7 tests are elaborated at

http://blog.fluturasolutions.com/2012/12/8-tests-to-decode-business...

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