Customer Attrition Analysis
Dec 1, 2012·
·
1 min read
Christopher Teixeira
I worked with team members to build a Bayesian Belief Network (BBN) on large data sources in Netezza to predict the likelihood of a person closing an account with our client. I compared the BBN model results against Logistic Regression to determine best modeling approach. The results showed that the Logistic Regression approach provided more accurate results, but required more resources to get that result.
Authors
Christopher Teixeira
(he/him)
Data Scientist
Christopher Teixeira is a Data Scientist with extensive experience applying statistics, applied probability,
and operations research to solve complex organizational challenges. Throughout his career, he has partnered with
diverse stakeholders to drive data-informed decision-making, helping organizations navigate the nuances of various
analytical techniques to find optimal solutions. Christopher has a proven track record of delivering code in multiple languages,
leading large-scale technical efforts, and responding to technical proposals and developing relationships with customers.
He holds an M.S. in Operations Research from George Mason University and a B.S. in Mathematics from Worcester Polytechnic Institute.