Charles Harrison - Diary of a Data Scientist
Charles Harrison

Charles Harrison

Charles Harrison is a Marketing Statistician at Salford Systems. In this role he uses his statistical modeling and computer programming background to illustrate the practical techniques and uses of Salford Software in real-world applications in tandem with our in-house marketing team.

Charles is a recent graduate from the University of Central Florida, where he earned his Masters of Science in Statistical Computing with an emphasis in Data Mining. Charles worked as an intern at Sprint Nextel in their Network Planning Division and later was a Business Intelligence Intern, taking his expertise to a new level by creating an infrastructure designed to analyze M2M data using SQL. He later improved upon his own software to map key geospatial traffic components to optimize the Sprint network. This work carried over to The J.M. Smucker Company where Charles was an internal consultant to marketing teams, providing them statistical analysis for time series forecasting, geospatial, and demographic analysis.

With advanced knowledge in machine learning, logistic regression, experimental design, and marketing, Charles provides actionable insights and valuable results to the Salford Team and translates them to an array of educational, promotional, and consulting projects. Outside of the office, Charles enjoys reading history and playing basketball.

Tuesday, 28 June 2016 09:46

Inside the Mind of a Statistician

"My process is very similar to that of any other analyst, so what makes a statistician unique? Our training. Most of a statistician’s training in applied statistics revolves around model building and diagnostics. Some of the things that we care a lot about (trust me, there are a lot more!) are assumptions, bias and variance, model selection, and properly answering questions."

Tuesday, 26 July 2016 09:34

The Costs of Misclassifications

I started to think about the consequences of medical misdiagnoses. What happens if someone has an infection and is told they do not by their doctor? What if someone does not have an infection but is treated as if they do? Which mistake would be worse?

 

Exploring the world of data mining and the triumphs and challenges experienced first hand from our in-house data scientists.

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