About this site

The Bayesian Bandit originally was a data science blog, sharing insights into different methods on how to solve business problems with data. Starting in October 2024, The Bayesian Bandit was enhanced to include more than just code and math. Now, The Bayesian Bandit includes stories and experiences from people in industry. The Bayesian Bandit aims to be the go-to location on how to become data-driven in your career, via demonstrated analyses and deep insights from industry professionals.

"Behind the Data": Our feature column

"Behind the Data" is the crown jewel of The Bayesian Bandit. As stated in our about page, we aim to help people discover and develop their data-driven careers by doing two things: demonstrating data science methods via analyses and by sharing insights from industry professionals who work in data-driven careers.

"Behind the Data" presents findings from interviews with a variety of voices in industry. Whether it be a seasoned data scientist or brand new MBA grad, we interview a variety of voices and present their insights to you so that you understand three things: how each individual has developed their career, the impact each has generated by being data-driven, and share different industries and their respective ways of being data-driven.

Who should read "Behind the Data"?

  • Anyone who wants to become more "data-driven" in their career
  • Anyone who wants to learn about industry standards for working with data
  • Anyone who wants to learn from industry leaders on how to grow their career

Meet our Authors

Brandon Scott

Brandon Scott holds a MBA from the Marriott School of Business (BYU), a MS in Statistics from Texas A&M, and a BS in Actuarial Science from BYU. Previously, Brandon worked as a Senior Business Analyst for AdvancedMD, working in sales and marketing analytics. After AdvancedMD, Brandon moved to Uber as a Senior Data Analyst to work in customer experience analytics for their new product, Uber Grocery. Brandon is passionate about helping people learn how to use data to solve problems and learning how others have crafted their own "data-driven" careers.