About me

I’ll try to be quick.  It will be difficult.

A brief note on what I’m doing now.  My time is roughly spent like this (waking hours):


Let’s say the vertical axis is hours of the day and the horizontal is something like months.  And repeat.

My formal education was in chemical engineering, go Missouri S&T!  I worked for a specialty chemical company and then for an oilfield services company.  Then my wife and I made a dramatic shift.  We decided to drive a truck together, over-the-road as it’s known.  49 states and 7 Canadian provinces.  We had a plan to do that for a set number of years, give or take few depending on actual results.  Now we have a little girl, and life is good.  Except for the fact that trucking (which I still do) isn’t particularly favorable to family life.

For a couple of years I taught math at a fantastic school in Northwest Arkansas.  Though it was a great experience, teaching wasn’t for me.  For the past year I have been teaching myself programming, and building a foundation in data science.


My history with computers.

In the Year of Our Lord, Nineteen and Ninety Two (8th grade), I vaguely remember programming an Apple IIe to draw several frames of a fish jumping out of water.  I was proud.  Of course I used MS Word and Excel later, but my next real exposure to programming was a C++ class in college.  I don’t remember what it was, but I did. Not. Like. It.  That was a shame because the instructor also taught Physics and I loved that.  I went on to copy and paste static websites and make them my own with small changes.  Huzzah!  I did some undergraduate research modeling supercritical CO2 on a UNIX system tweaking my professor’s Monte Carlo simulations.  Until then I thought it was just a car.

It wasn’t until June of 2015 that I did a simple Python course on Codecademy.  That was cool but I didn’t “catch the fever” until I took David Malan’s CS50 MOOC from Harvard/Edx.  For most of the course I learned the basics of C.  Then some web programming – Javascript and PHP, interacting with a MySQL database, and using APIs.

Anyone will agree with me when I say this:  After using C (which I love), using Python is a dream.  That’s how I got interested in data science.  Python has amazing libraries (and a thriving community) for data science.  So my focus has been getting better with Python, and learning everything I can about statistics, analytics, visualization, and machine learning.