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Hello! I am interested in becoming a data scientist and am in the process of deciding on an educational path to pursue. I would love to get the perspectives of current professionals, recruiters, and employers on the following questions: 

  • How do you view graduates of master’s programs in analytics (e.g. UC Berkeley’s Master of Information and Data Science)? Are they any more or any less qualified for data scientist roles than their peers who obtain graduate degrees in computer science, physics, biology, etc.?
  • Are data scientists considered for executive roles (CEO, COO, CMO, etc.), or are they generally entrenched in the data silo and pegged as experts in that field alone?
  • Are graduates of MBA programs with a concentration in business analytics viewed as capable data scientists? If so, are they any more likely than their peers who lack MBAs to move into managerial positions, potentially non-data-centric ones?


Thank you!

Tags: CDO, CEO, CMO, COO, MBA, UC Berkeley, advice, careers, education, management, More…master's

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Many data scientists have become executives, some even billionaires like the CEO of SAS, or D.E. Shaw (hedge fund). Usually their job title change, though some become chief data scientist or CDO. In my case, my job titles are executive data scientist and co-founder.

To answer your last question, Google my article 'high versus low level data science'. MBA's fit in the high level category.

Thank you for the response, Vincent! In your experience, are there many low-level data scientists who are also the decision makers? I am interested in acquiring the technical foundation of low-level data science, but I don't want to be strictly thought of as the "data geek" who turns over his results to decision makers for them to ultimately choose the course of action.

Also, do you have any views on the emerging data science master's degrees being offered by such universities as UC Berkeley and Northwestern?


Vincent Granville said:

Many data scientists have become executives, some even billionaires like the CEO of SAS, or D.E. Shaw (hedge fund). Usually their job title change, though some become chief data scientist or CDO. In my case, my job titles are executive data scientist and co-founder.

To answer your last question, Google my article 'high versus low level data science'. MBA's fit in the high level category.

Thank you so much, Jason! This is really helpful information. Do you have any recommendations as far as how to break into a role in data science now so that I can begin to acquire experience and gain some on-the-job training?

Jason said:

Hi Nadav, the answer to this question can change drastically based on the industries you are looking at and your current experience but will give it a shot.

 

For quick context, I hire and manage PhD and Masters level data science candidates but come from the MBA side. Prior to this role I did my undergrad in IT, worked in management consulting and then some investment banking. Have always been naturally data-driven with a love of technology but had to learn the "hardcore" stats on the job (used to rebuild SAS models in R at night to both learn the methodology and the language). Alright, on to the good stuff!

 

How do you view graduates of master’s programs in analytics (e.g. UC Berkeley’s Master of Information and Data Science)? Are they any more or any less qualified for data scientist roles than their peers who obtain graduate degrees in computer science, physics, biology, etc.?

 

I think they are great indicators of interest and have worked with a few candidates from these programs that did very well. However, I tend to give more weight to projects (and prior experience/results, if applicable) when choosing between candidates. In other words, these programs may help get you get an interview but will not get you the job.

 

Are data scientists considered for executive roles (CEO, COO, CMO, etc.), or are they generally entrenched in the data silo and pegged as experts in that field alone?

 

Highly dependent on the industry and life cycle stage of the firm (start-up, Fortune 500, etc.). Today, across all industries, I'd lean towards generally entrenched in the data silo. HOWEVER, I think this will change over the next 5-10 years as understanding and applying data is more of a competitive advantage versus just owning data. As you become more senior though your time will most likely shift from low-level to high-level analysis if you want a more general C-suite role.

 

Are graduates of MBA programs with a concentration in business analytics viewed as capable data scientists? If so, are they any more likely than their peers who lack MBAs to move into managerial positions, potentially non-data-centric ones?

 

Generally no. I was lucky enough to network into the role and relied heavily on my strong business and engineering background to carry my weight as I was learning the stats. You will never "out-math" a PhD and if someone comes in thinking they know the science at a deep level (you won't after taking 3-4 elective courses) it's going to get ugly fast. The flip side is you generally come in with a broader skill-set and will eventually be able to help translate between disciplines (even among PhDs as different disciplines sometimes rely on different methodologies and terminology).

 

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