Even a casual look around the web at what makes a good data scientist will reveal that many feel that a great data scientist is a unicorn: an entity that blends a unique and disparate set of skills and traits to perform what can appear to be magic with really big sets of data. Somewhat to my surprise, it turns out that I have aspirations toward wizardry.
How I Got Here
I recently moved to Houston, TX from Wasilla, AK. In Alaska, I worked in the telecommunications industry for nearly 20 years, from February 2000 until July 2018. We moved because my wife, who works in the oil and gas industry, took another job that was based in Houston.
In the course of looking for employment in my new city, I came to realize that I was dissatisfied with my job. It wasn’t a bad job. In fact, I had previously enjoyed it and it did feed my need to be constantly learning. I just felt that I needed a change from poring over packet captures and digging through signaling protocols.
I have always had an interest in programming. Toward the end of my time in Alaska, I had taught myself enough Python to script some job-aid tools to streamline some tasks. I found that I really enjoyed this. It was apparent to others, as well. One day, after I solved a problem in a text-parsing script I had written, one of my co-workers told me “You know, Dave, maybe you should go back to school for that. You seem to really enjoy it.”
Fast forward to the summer of 2019. I’m contemplating yet more job listings on Indeed and I get to thinking about my co-worker’s comment. I had previously seen advertisements for coding bootcamps but now I started looking at them in earnest. In the course of that investigation, I ran across a data science program.
Reading about this program excited me far more than the coding program had. Tempering my excitement, I looked into the data science field to ensure it was a good fit for me.
What I Determined
There are many articles on what makes a great data scientist. None of them align perfectly, though there is some general overlap. Some of the points of overlap I found were:
- Curiosity
- A love of learning
- Analytical thinking, especially with regard to solving problems
- Tenacity or determination
- Diverse technical skills
- Education, especially in statistics and math
I have the curiosity, tenacity, love of learning, and problem solving mindset. I lack the education and some of the technical skills, but I can learn the material and develop those skills. Importantly, I was still interested in the field after my preliminary research, so I decided to move forward.
I am not a unicorn, nor a wizard, but someday soon, I’m going to make that transformation.
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