Update for January 2023

I’m now a Data Scientist at LinkedIn focusing on creating data products and customer value for our LinkedIn Marketing Solutions (LMS) business. This post was originally written in 2018 when I was committing myself to learn and pracitce Data Science, having no idea that I would ever get to where I am now. I’m grateful for the right combination of opportunity and luck that I’ve had along the way. I’m also grateful that almost five years ago, I made this committment to my craft and to becoming the professional I wanted to become. For those out there aspiring to something that feels out of reach, you can do it… make the committment and start taking incremental steps today, because in the end they will amount to your dreams fulfilled.

Original Post

I’ve recently begun a journey, one which I see more and more people embarking on in the ever more data-centric industrial world. My journey doesn’t have a particular ending, nor can I recollect a distinct beginning. It can more aptly be described as where I’ve ended up after a recurring, proverbial “bouncing off of various brick walls” until I figured out what I wanted to do when I grow up.

Several years ago, I was working in finance. It was the finance of the personal variety, centered on sales, and for me, centered on compromising often what I believed was best for my clients in order to keep my job. After all, if you aren’t filling all of your sales buckets, you just aren’t doing it right. Tisk tisk. Days, weeks and months began to pile up where I contemplated where my career and life was headed. I found myself often unhappy and unfulfilled. After spending 3 years in finance, I decided to leave my position in pursuit of something different, although I wasn’t entirely sure what that would be at the time.

It’s a common human theme to try and understand what motivates us, what our purpose is and how we can do something that we love professionally. Although I don’t have the complete answer to these questions, I feel I’ve gotten a bit closer over the years. It all started with taking the uncomfortable step of freeing myself from a career I didn’t enjoy in pursuit of greener pastures, wherever those may be.

My post-finance chapter involved me meeting a girl (who is now my wife) and moving to Colorado, where I got a job with the U.S. Department of Veterans Affairs, and decided to go back to school. More specifically, I decided to pursue a graduate degree in Economics. I’ve always loved math, I enjoy economic theory and understanding why people and entities make the decisions that they do, and I imagined that such a career choice would be a lucrative one. So, I took the GRE, and enrolled at University of Colorado, Denver in the M.A. Economics program.

Graduate-level Economics at CU Denver is a quantitatively-focused degree, with an emphasis on mathematical economics (linear algebra and multivariable calculus), research methods, and statistical programming (STATA, SAS, R, SPSS). I feel extremely fortunate to have been exposed to both the breadth and depth of material that was covered throughout the curriculum. The journey toward completing the M.A. Economics program was extremely enjoyable and fulfilling. Although, somewhere along the path, I had to start thinking about what I would do with my degree once I had it.

Months went by, and as I obsessed over job postings for Economists, I realized that practically all of these positions involved a move to Washington, D.C. and working for one of the Federal Institutions therein. I believe that there are some real benefits to having a career in D.C., although having spent a combined seven years in the military and working for the Federal Government, I was ready to try something different in my career. I know people who have “done their time in D.C.” and were anxious to escape the hustle, bustle, and the politics, post haste!

And so… I wondered, if I’m not going to work as an Economist in D.C., what else is there? I started looking at what others in my academic cohort did professionally, and realized… quite a few of them are in Data Analytics and Data Science.

It didn’t take me long to realize that many of the things I loved about Economics were staples of the Data Analytics world as well. Statistical analysis, decision science, helping discover insights from data to be consumed by decision-makers. I enjoy all of it. So I put together a curriculum, based on some of the other “Data Science Masters,” and “How to Become a Data Scientist” articles out there.

Over time, I’ve worked through each piece of my created curriculum with a focus on what was most relevent to me at the time, based on either work projects or personal interest.

For the computer science material, I watched all of the course videos and performed exercises as they were being explained, and completed as much of any problem set as I deemed necessary to adequately comprehend the material. Exposure to material and concepts is my key focus in this domain. For the data science material, I focused more on completing exercises and projects as directed in the coursework. My goal here was to both master the material and put together a portfolio of projects. My goals put simply is to be a great Data Scientist and a competent Computer Scientist.

A few of the first courses are outlined below, and I have shared and will continue sharing more detail regarding some of these courses in other posts.

Please feel free to provide any feedback or advice, and stay tuned for further details and my approach to learning these skills.

Thank you for reading.

INTRODUCTION TO COMPUTER SCIENCE AND DATA SCIENCE

Data Science: Become a Data Scientist (Completed) https://www.dataquest.io/path/data-scientist

Introduction to Computer Science – CS50 (Audit Completed) https://cs50.harvard.edu/

Introduction to Computer Science and Programming using Python (In Progress) https://www.edx.org/course/introduction-computer-science-mitx-6-00-1x-10

Next (Data Science):

DataCamp Career Tracks (all) https://www.datacamp.com/tracks/career