The Art of Data Science

The Art of Data Science: How a Real Data Scientist is a Renaissance Man (And Why You Can’t Live Without One) 

“Data Scientist: Sexiest Job of the 21st Century.” It certainly has a nice ring to it, doesn’t it? The question lies in: how could a job with both the words ‘Data’ and ‘Scientist’ be considered the sexiest job? Studying economics, sitting at the computer running code, and talking about data issues with a supply chain analyst over drinks. This does not seem like the path to the sexiest job. It sounds more like a path to becoming the King of the Nerds.  So what does a “King of the Nerds” do that’s considered so alluring? Well, it may surprise you to hear that data science is as much art as it is science. Though the paintbrushes have been exchanged for keyboards, a data scientist innovates like the people of the Renaissance. We sit at the intersection of a variety of data to discover connections never found before through advanced analytic techniques, such as machine learning and artificial intelligence.  

But in a world of growing complexity and data driven business, the skills of a data scientist have grown to be extremely valuable. 

Companies are offering highly competitive salaries for these roles and the list of openings continues to grow. The true power of a data scientist is not in being able to write a program or tell if something is statistically significant; these are merely the tools. The ability to tell the story of the data and communicate value becomes the key that a data scientist holds

In an interview for my first job after college, I was asked about a data-intensive project I had worked on. I was ready for this exact question. I fully explained a project I worked on about creating a quality of life index for over 100 U.S. cities. It went into detail on the economic theory, the past studies, data sources, and the hard programming skills I learned. I thought that should seem rather impressive, and when I was finally done, there was only one question, “how can I use what you learned in this business?”

This was not something I was expecting. I came up with a logical answer on the fly, but it was a major learning moment. Through the project, I learned to write in R, SQL, and how to work with messy data.  But from this moment, I learned the one skill I would go on to growcommunicating value. The data scientist paints the picture. If no one can see the picture or its value, you’ll inevitably get the follow up, “What’s the point?” 

In Supply Chain, or Value Chain, depending on your preference, we hear the buzz words associated with the work data scientists do: Big Data, Machine Learning, Artificial Intelligence, Internet of Things. The question becomes: where is the value? In an industry where the volume of data and diversity of data sources is increasing at an unprecedented rate, getting lost in the data lake that is amassing before you is easy. This is where the data scientist comes to help; they can swim through this lake and find the value beneath the surface.  For example, automatically generating forecasts that include the impact of your product promotions and marketing. Or determining that you should order 25% more sugar before dooming weather will cause a supplier delay. Or suggesting how to promote expiring products in a way that mitigates inventory waste. The possibilities are wide open, once you find the talent. 

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