I have tasked with building a team of data scientists over the last few months. As I come with a consulting background I have a very different orientation to business outcomes relative to the team of statisticians and "big data" guys we normally hire. I have been asked at multiple forums about why I have been able to get results and communicate without loading up on jargon... here is my attempt to share my insights over a series of blogs
While we will discuss algorithms and statistics, the focus will be more on how we deliver business outcomes- bridging the chasm between academic theory and business needs.
While Data Science is seen as a geek subject with loads of jargon- statistical mumbo jumbo, Hadoop, Big Data analytics and the like- I believe the need is never greater for the integrators. The specialists who can understand the business context and determine how to achieve it using the new tools. The difference from a typical technology view is that each of the domains is very different and a basic level of breadth is required to pull together the pieces
Hope my thoughts are useful and I look forward to your comments!
While we will discuss algorithms and statistics, the focus will be more on how we deliver business outcomes- bridging the chasm between academic theory and business needs.
While Data Science is seen as a geek subject with loads of jargon- statistical mumbo jumbo, Hadoop, Big Data analytics and the like- I believe the need is never greater for the integrators. The specialists who can understand the business context and determine how to achieve it using the new tools. The difference from a typical technology view is that each of the domains is very different and a basic level of breadth is required to pull together the pieces
Hope my thoughts are useful and I look forward to your comments!
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