The Data Scientist Algorithm

The following is a guest post. What is the make-up of a data scientist? Is it all about the amount of knowledge one possesses? The specific area of study? To answer these questions, Software Advice, a website that researches and compares BI tools (check out their guide here), decided to examine the top performers on Kaggle – the largest data scientist community in the world.

Kaggle offers an online platform that allows companies to connect with data analysts from around the world, who then compete in the company’s big data challenge (often for prize money or a job). Below are the findings from the analysis of the top 100 prize-winning Kaggle performers (as of October 15, 2013).

Stay in School

Educational background was directly correlated with success in competitions. With over 80 percent of the top 100 Kaggle users having a Master’s degree or higher, depth of study was also a common indicator of top-level winners. Additionally, 35 percent of the top performers had a Ph.D.

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Don’t Stress the Major

As expected, the top areas of study among these data superstars included computer science and mathematics. While these programs of study are of no surprise, others came up that suggested a more diverse background was as popular as an expected one – areas of study ranged from economics, to philosophy, to even law.

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This analysis indicates there is no “formula” to create the ideal data scientist; these data “wizards” come from all walks of life. If anything, practice does make perfect – there was a strong correlation found between amount of contests entered and competition wins.

Read the full report on Software Advice’s Business Intelligence blog, Plotting Success.