Everyone knows resumes are suboptimal, at best. It is truly odd that in this era, where websites exist and are pervasive, we still spend time adjusting the wording and formatting of this account of what we’ve done professionally so that it can fit on a single printed page - especially in the tech industry!
Here, I’ve tried to simply describe, in plain English, what I’ve done at the jobs I’ve worked at. I have also links to the profiles of the people I’ve worked with where appropriate.
Unfortunately I don’t have many GitHub links since the work I’ve done for these companies - especially Trunk Club and Metis - is proprietary. Still, I have extensive GitHub links and project descriptions on side projects I’ve done in the Neural Net Tutorials and Data Science Resources sections of this site.
I taught the Spring and Summer 2017 full time Data Science Immersive programs. My manager for the immersive programs was Debbie Berebichez. In the Fall of 2017 I’ll be working on corporate training - I’m currently scheduled to lead multiple three hour workshops at major universities on the East Coast in September (through Metis). My manager for these will be Mike Galvin.
Teaching these bootcamps has been incredibly beneficial to my development as a Data Scientist:
I worked at Trunk Club from December 2015-March 2017. There, I worked within our Python Data Science Stack - Pandas, Numpy, Sci-Kit Learn, Flask etc. - to build a deploy a variety of models, touching on everything from marketing optimization to clothing recommendations. I was the first Python Data Science hire, so I got the experience of working independently and teaching myself a lot - three months after I started, we hired Scott Cronin and Zac Ernst, both of whom I learned a ton from over the following year.
My main manager at Trunk Club was Justin Hughes.
I did lots of analyses of credit card data, built Tableau dashboards to let my teams see the key metrics, and made lots of presentations making recommendations based on these analyses to VPs, especially John Munn, who I knew well while I was there.
While I was working at Capital One, I took every opportunity I could to use Python in my job, eventually automating many of the analyses I was responsible for using scripts. This ended up being a great, practical way to learn the fundamentals of data manipulation in Python, especially Pandas.
My manager for most of my time at Capital One was Joe Crowley.
I was extremely passionate about Udacity courses during 2015, while I was working at Capital One and learning programming/Data Science on the side. So, they created a part time role for me that I did remotely while working in Chicago, called “Course Support Specialist”.
I hosted one-on-one coding help sessions on forums with students, reviewed Udacity students’ Python projects and gave them coding advice, and wrote supplementary content for Udacity’s introductory Python and Java courses - I did the Java courses as well since they needed _someone_ to do it!