Hey there, I'm Brian. I'm a 14 year veteran of the Data Sciences, formely of Target. Previous projects have been all over the board, from demand forecasting, pricing, through personalizing recommendations on Target.com. But other projects include using graph computation engines to perfect CRM and good old-fashioned promotion optimization. As of Winter 2020, I'm actively practicing Deep Learning, doing research in Natural Language Generation and other various applications of Machine Learning. In my previous role at Target as a Data Analyst, I was brainstorming new ways to leverage Target's sales and customer data to extract customer insights and deliver on our "Expect More, Pay Less"​ brand promise. In the past, this has involved statistical analysis methods such as principle component analysis, naive bayes classifiers, and various decision tree algorithms. These sorts of sophisticated analyses translate directly into buyer decisions, making Target the world class retailer it is today.Prior to Target, I worked for UnitedHealth Group learning about the realm of healthcare data. I've studied DRG systems for paying inpatient hospital claims, learned to reverse engineer provider contracts within the data systems, and worked on a trend detection system to help focus my department's time on investigating areas where fraud appears to be emerging. Find me on brian.copeland.bz for more!