I love to learn in general, but mostly I am a data fanatic - I love reading, writing, and learning about all things data: science, analysis, and visualizations.
Background
I fell in love with data when I got a gig as a data analyst for Comcast’s Xfinity Connect residential email team in 2014 after 5 years as a project manager. In that role, I was responsible for detecting compromised user accounts that were being used abusively - sending spam and doing other nefarious things with Comcast accounts. While I was still very new to data, I did manage to implement some cool detection algorithms in a pretty creative way - I implemented a logistic regression in Splunk. That process is still in production today, though the team has since made it way better!
From there, I moved internally to Xfinity Mobile’s (XM) Risk Management team - this was in early 2017. Currently in this role, I focused initially on the detection and remediation of fraudulent purchases - along with reporting. Combining data engineering, analytics, and science, I (along with a great team) built a tool that combines feature creation, statistically and business-based rules, and predictive models in real-time to allow the best customer experience while purchasing phones in all sales channels.
I have recently shifted focus from fraud to credit - learning the ins and outs of lending. So far in the new focus, I have spent my time baselining (building out our reporting suite) and forecasting performance based on our evolving strategy changes.
In addition to data, I love being the father of 2 fantastic children and husband to a remarkable woman.
Interests
- Data Science, Analytics, & Visualizations
- R & Python
- Tableau
- Splunk
- Being a dad
- Being an uncle
- Sports (soccer, basketball, golf, running, & cycling)
Education
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MS in Applied Statistics, 2017
Villanova University
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BS in Business & Engineering, 2009
Drexel University
