After one and a half years of freedom and no homework, I find myself ten weeks into a two year part-time online Master’s program. If you had known me in my final year of college, you would know that I was ready to be finished with school. The never-ending due dates and stress from maintaining my grades just wasn’t appealing . You would have known that if something ever drove me back to school, it would be an MBA, not an MS in Data Science. So, what changed?
I was Unsatisfied with My Current Job
Since graduating in 2019, I’ve been working full-time as a Software Developer. For some, that might not seem any different from Data Science. It’s technical, I code, and there’s millions of different directions I could go. Just to scratch the surface, I could build websites, create applications, or maintain software.
In fact, I’ve had a lot of variety in my job as a Software Developer. In just a year and a half, I’ve worked on five separate projects, each with their own unique languages and skills I had to implement. Regardless, I still felt like something was missing.
I realized that whenever I talked about my job to my friends, it was always “I fixed this bug”, “I added this functionality”, or “I reviewed some code”. Sure, it was never the same bug, functionality, or piece of code, but the overall process felt stagnant. Every new task I was handed felt like a different version of the task I had just completed.
Even so, I didn’t want to stop coding.
I felt stuck. I spent a lot of time asking myself the same rhetorical questions on repeat. What am I doing? Is it time to jump ship? Maybe I can look into switching teams? Where do I go from here?
Commence the scrambling. Once I realized that I really wasn’t happy with where I was, I did what any other coder would do. I googled. Whether it was MBA programs, new job postings, other careers that involve coding, or what others do when unsatisfied with their work, anything relevant, I googled it.
Of course, I came across the Data Science field amongst my search. It’s an extremely “sexy” field to be in right now. As a programmer, it’s constantly suggested when I look into a career change. However, I wasn’t convinced. In my mind, it felt like it would be more of the same.
Like Software Development, Data Science is also an umbrella term. Business Analysts, Data Engineers, Machine Learning Engineers, Statisticians, Data Analysts, and Data Scientists can all truthfully claim to have a career in Data Science.
With that in mind, every article I read that mentioned Data Science seemed very surface level. In every article, it was simply data gathering → data cleaning → data transformation → data modeling → data visualization → communicate results, and repeat. In addition, each article mentioned the importance of mathematics and statistics, two subjects I struggle with.
Data Science was Constantly Evolving
The turning point for me came when I started diving into my company’s machine learning Slack channel.
The channel consisted of articles upon articles of new ideas, methods, and applications of machine learning. Many of them went over my head (ex. Using DeepSpeed and Megatron to Train Megatron-Turing NLG 530B, the World’s Largest and Most Powerful Generative Language Model). However, the interest my coworkers demonstrated in the channel kept me reading and I began to understand the different facets and impacts of Data Science.
I’ve included some of my favorite articles below:
- How Artificial Intelligence Completed Beethoven’s Unfinished Tenth Symphony
- Artificial Networks Learn to Smell like the Brain
- Saving Seaweed with Machine Learning
The further back in the channel I would go, the more outdated the articles became. For example, I read articles about how a model called T0 outperformed GPT-3. Then I’d see an article from months before about how GPT-3 dominated the previous top model and was powering the next generation of apps.
Growing up in an era of technology, I am well aware that it advances at a rapid pace. That didn’t stop me from being in awe when I read it for myself and saw how quickly something “better” came along.
Data Science was Exploratory
I began talking to my colleagues about their work, and everyday their answers changed. Although I cannot divulge my colleagues’ projects, I can say it was never “I fixed this bug”, “I added this functionality”, or “I reviewed some code”. Their responses resonated with me.
With my newfound interest, I went back. I went back to the articles I had originally labeled surface level. I went back to the process that felt like more of the same. I read them again, this time, with a different perspective.
As a Software Developer, I know I make an impact. Organizations and individuals alike use the software I have created for their own projects and needs. However, there was no insight, no discovery, no answer, and no conclusion. There was only an end product.
That’s when I realized what was missing: an investigation, an analysis. At first, the word analysis just sounded like a repetitive process as I previously mentioned. I realized that was wrong.
I talked to my coworkers about the process overall. As they painted a step by step picture, I imagined myself doing the same process and felt excited. Sure, the data preparation and cleaning sounded tedious. Yet, when the actual analysis began and they finally looked for insights and patterns, it sounded like it was all worth it.
It didn’t hurt that even projects with non-conclusive analysis can still provide some type of insight. So there’s always something to be gained.
With an I might as well try attitude, I decided to give Data Science a go.
I Needed Structure and Accountability
Naturally, after becoming curious about the subject, I began teaching myself. I wanted to understand the terms and algorithms I saw in the articles. I bought myself a popular textbook and planned out many personal projects. Unfortunately for me, I have no discipline. When left to my own devices, I usually find myself on my phone in bed.
I constantly thought about the ideas I had and the things I needed to do, but I didn’t do them. Probably not the best characteristic, but alas, that’s me. Thus, I decided that a formal education that would hold me accountable with all those stressful due dates and grades was the solution to my problem.
To Gain Authority
I have plenty of one on one meetings with my managers to check in on my progress. During one such meeting, I asked “How can I switch into Data Science?”. Luckily for me, my manager was extremely helpful. She explained the learning programs our company offered, mentioned the Data Science work my current project needed done, and even offered me the work. Of course I said yes. Unfortunately, that was months ago, and there was no follow up.
I didn’t take it personally. I wasn’t qualified and there were plenty of other variables at play. However, it also made me more determined. If I wanted a transition in life, I needed to be proactive – and obtain more advanced knowledge in the field.
Compared to online courses and being self-taught, I felt that a Master’s would give me more credibility. With a Master’s degree, I hope to be taken more seriously in meetings. I hope to have more say in what kind of work I do. I’m not saying a Master’s degree will guarantee that, however, the possibility was another big motivator for me.
I Had the Means
The biggest thing holding me back from a Master’s was the money. I had some money saved up, but certainly not enough to cover all of it. Was it worth the price?
Jury is still out on that one. I can’t say that I would have chosen my current program if I didn’t receive help. While telling me about the learning programs in our company, my manager thankfully informed me about the reimbursement policy as well.
With the help of my company and what I had saved up, it was a lot easier for me to make the decision to pursue higher education.
To Have a Sense of Personal Accomplishment
Lastly, my entirety of experience in the industry has been from home and during a pandemic. With little human interaction and being cooped up in the same room for hours on end, I tend to lose track of time. I felt like I had done nothing with my life in that one year, and not to get too somber, but it felt like time would continue to slip away if I just carried on with my routine.
I wanted to challenge myself to tackle those pesky subjects that toyed with me in college.
I wanted to meet new people and experience those small interactions by conversing with my classmates.
I wanted to learn.
I wanted to commit myself to something.
I wanted to earn a Master’s Degree in Data Science.