Subscribe to our Newsletter

So, You Have Become a Data Scientist... So, You Have Hired a Data Scientist

Every day brings news about near universal acceptance of Data Science as a mainstream inter-disciplinary professional field and about emerging partnerships between innovative universities and #BigData and #Cloud technology vendors.  Reportedly, there will be 4.4 million new #BigData related jobs created worldwide by 2015.  Just a week ago IBM announced new academic collaborations with universities across the globe, focusing on #BigData and #DataAnalytics http://ibm.co/18ADeBU.

Increasingly, companies and organizations of all types and sizes are crying S.O.S. about growing shortage of qualified #BigData and #DataAnalytics professionals.  #DataScientist is now a common job title, and a mix of #DataScience education and experience is required to qualify. 

But a lot of companies eager to employ Data Scientists have not created conditions for their maximum success.  #BigData and #BigDataAnalytics is not an evolutionary change.  In many ways, it is a disruptive paradigm shift and game-changing avalanche of new enabling capabilities.  Unless companies and organization adapt their business processes and structures, they will end up with yet another organizational and data silo, in which innovation is starved and #BigData and #Analytics opportunities are wasted,

So, if you hire a Data Scientist,

  1. Where will she/he fit in the organizational structure?  What will be her/his sphere of influence?
  2. In what areas will she/he be involved as a stakeholder? 
  3. How will her/his work fit in the project plan, Agile IT and Engineering process?
  4. Will she/he be a manager, an individual contributor, a product manager, or a "go-to" person without organizational affinity?
  5. Who will she/he report to? Who will be her/his peers? Will she/he be teamed up with engineers, other data scientists, or anybody else?   Will she/he be part of a Scrum team?
  6. Is the present organizational structure and culture conducive or detrimental for her/his job success and how willing and ready is the company or organization to adapt, change, or even restructure?

If you are a CXO and don't have answers to these questions, time to roll up sleeves. 

Views: 1294

Tags: #BigData, #BusinessProcess, #DataAnalytics, #DataScientist, #Management

Comment by Hilda Cerdeira on August 26, 2013 at 10:17am

I believe the possibility to discuss the work with peers is extremely important. But this will be a problem for companies who do not expect to spend  so much in this type of personnel.

Comment by Rob Pakulski on September 17, 2013 at 11:36am

I have built a team for the purpose of "Big Data."  These questions are highly relevant and definitely are the right questions.  Beware, just answering the questions is not enough, the answers need to be reviewed and vetted.   Working with those in your network that have experience will go a long way.  Thinking back to the early stages of building the team I would answer these questions one way.  However, if I answered these same questions today, my answers would be very different.  A CXO in the early stages, who is either building the team for the first time or around a data scientist, will want to focus on how data gets in, how data will be processed, and how to ensure actionable information comes out.

Comment

You need to be a member of BigDataNews to add comments!

Join BigDataNews

On Data Science Central

© 2019   BigDataNews.com is a subsidiary of DataScienceCentral LLC and not affiliated with Systap   Powered by

Badges  |  Report an Issue  |  Privacy Policy  |  Terms of Service