There are two reasons I have chosen to learn about Data Science. The first reason is not as “feel good” as the second. Let me begin.
I wish I could tell you that I am doing this out of pure interest. I most definitely AM interested. But more on that shortly.
I call myself a “software engineer”. I am self-taught. Correction: I WAS a software engineer. But that officially ended in 2017 when I was laid off. Before that, I had been in the industry for more than 20 years.
After being laid off, I did some freelance work for a little under a year. Contracts dried up and I dove right into my job hunt. There are details but I won’t let them bog down this short story I wish to tell. Just know that the consensus seems to be that getting laid off in the Tech industry is difficult to recover from for my demographic. I was 46 at the time. Heck, it’s probably just as difficult for any “professional” to recover from getting laid off in one’s late 40s. Long story short: after almost a year of intense (read: frequent) interviewing, paired with the patterned “you’re overqualified” rejections, I can confirm this.
Now, this is where my story differs from all those articles claiming the interviewing process is broken in this industry, or that this is a young person’s industry. Maybe all that is true and at first, I must admit, I wanted to believe that. I wanted to believe that perhaps my plight was due to “ageism”. It wasn’t me, right?
I am not here to make excuses. The truth is that while I was gainfully employed I simply got cocky. My title at the time was “Senior Software Engineer”. I had that title for more than 10 years. I thought I was untouchable, even invaluable. With this attitude, I willfully ignored the FACT that, in our industry, one must always be ever-evolving one’s skill-set if one wishes to stay relevant. I STOPPED LEARNING!
THIS WAS MY FAULT and nobody else’s; not a broken interviewing process, nor ageism. The fault was mine.
But that only explains the first part of how I eventually decided to pursue Data Science. Understand that it took me some time to come to acceptance of the above. Once I accepted this as a fact, I was ready to get to work. I knew that my first step was to begin the journey of updating my skill-set, to get “up to speed”. But where to begin?
The thing is, I have a background in Mathematics, having studied Pure Mathematics at Cal. State University, Long Beach. Also, without going into too much detail, when it became painfully obvious that interviewing as a Software Engineer wasn’t working out for me, I found myself thinking in the back of my head, “You know what would be fun? Writing programs to analyze numbers in a lab somewhere!”
I guess I just didn’t realize at the time that that idea falls under the Data Scientist’s umbrella. It seems obvious now, right? Additionally, late in my career as a “Software Engineer”, I made a few “Data Scientist” friends, some of which even worked in the same department (Engineering). There were many occasions in which, when I should have been working on coding that RESTful web service, I got to talking to my Data Scientist friend about her project. Before I knew it, half of the afternoon was gone. My point? In the end, I was more interested in this Data Science stuff than MY work.
So, fast forward to 2 years later, after my lay off, and Data Science simply makes the most sense for me. Of course, I am utterly fascinated by all that I have learned so far on this path to Data Science “Enlightenment”. And, of course, Data Scientists are one of if not the most in-demand professionals in the Tech industry. But for me, it’s about more than just getting a job, now.
Every day I GET to learn new stuff about this fascinating subject. I am only at the beginning of the process but every bit of it is fun. Numbers are fun. Statstics is fun. Graphs are fun!
Admission: I LOVE to write math proofs. Yep, I’m a geek alright. Everything I have learned about Data Science so far feels the same as when I am working through a rigorous math proof. We are given a question to answer. We justify it with logic, numbers, and math. We document our work to share our “proof” and justification for our conclusion with others. We get to do all of this great stuff and people are actually interested in the results?! You mean to tell me that someone other than my math professors wants to see this kind of stuff? SIGN ME UP!
Today, I am happy. I am excited for what new adventures in Data Science await me tomorrow.