The Best Advice I Received About Pursuing A Masters In Data Science

Payton Soicher
6 min readJun 2, 2023


College campus using generative AI

One of the best decisions I made for my career was pursuing an online masters degree in analytics from Georgia Tech. I was able to do it on my own time, finished it within two years, and was able to complete it without breaking the bank. Receiving a masters degree was not something I actually ever planned on getting. Running out of the room from my last undergrad final exam, I was relieved to be finished with the long nights studying and finally thought it was over, I didn’t ever have to open up another textbook.

Well, fast forward 10 years and now I spend a lot of my time reading textbooks, white-papers, and watching video tutorials on solving some of the toughest challenges I come across in my data science career. It has become more of a passion than work. Although it is not explicitly written, I understand continued education in the data field is needed in order to do my job to the best of my abilities. I’ve evolved past my 18 year old self, as hopefully most of us do. I don’t have to attend unnecessary electives to complete a degree, but rather get to identify the things I know will take my skills to the next level.

To me, on the job experience has by far been the best education I could have received; however, that is not exactly how corporations feel all the time. Go ahead, go on a job search and look for something at the senior level or an executive level and tell me what you see. Let me show you a few screenshots I’ve taken from some job searches:

Personally, I think there is a magnitude of problems requiring higher education as requirements to be eligible for a job, but at the same time, I get it. From a corporation’s side, you want to hire smart people for roles. A lazy way to make sure you get people who have met a minimum “smart test” is just to see which people have received a degree in higher education. Those who read it and don’t have one will most likely move onto the next one, leaving a smaller pool of candidates who have more education background but maybe less relevant experience.

Who knows how many great candidates have been dismissed because of a advanced degree requirement that wasn’t really necessary?

This was the pickle I got into when I realized I wanted to work my way up the data science career path. After about a year of relevant experience and checking to see what else was out there, I realized I kept seeing the dreaded masters or PhD minimum requirement. Was I really going to hit into a wall on all my applications because I only had a bachelors degree? Did I really want to put the time and energy into studying and taking tests again for years in order to overcome being overlooked? Was it worth it in the long run?

After taking some time to reflect on whether I really wanted to get back into late night study sessions, a family friend asked me what my goals were for the next few years. I told him I was enjoying my job so far in data science, and I was thinking about this next step by getting a masters in a data science related field. It had only been a few months after I graduated. I told him there were a lot of different pathways forward in my career, but this one would jump start it the quickest. Might as well get a start on it now before I get too caught up in the progression of life.

In simple words, his response changed my whole outlook on the entire thing:

“Make sure you actually like it first”

I was brand new to the field! How many people have decided too quickly to jump into a career path they didn’t actually end up using? I am one of a few people I knew who was still even utilizing their undergraduate degree, and the others seemed to just get a degree in something they thought they liked and by the time they put on their graduation gown, they weren’t so sure of their decisions anymore. I know a few people who already had their graduate studies planned prior to ever working in the field, just for it to be a waste of time in the end. What isn’t taught in classrooms is the difference between learning about how something works, and actually identifying if you like to do that kind of thing.

One of the unique benefits about a graduate degree is there is no “expected” timeline. It’s not like an undergraduate path where there is a societal expectation to start immediately after high school. It makes more sense to take advantage of this timeline rather than jump into something too quickly. Making a decision on what school you want to attend is a tough question before throwing in other factors like time and money. The least you can do is make sure the subject area is something you thoroughly enjoy.

I took that advice as a sign to slow down and make sure I knew I wouldn’t be caught in the middle between no longer being excited about finishing the degree, or completing my degree with a sense of accomplishment and knowing I would be better off in my career due to it.

It took me about three years of working in data science before I recognized how much I loved working on the business side of applied machine learning rather than generative machine learning. I found a passion for analyzing problems and creating unique solutions rather than the research of how to build newly formed predictive models with no real business application. Thats why I ended up getting my masters degree in analytics focused in business rather than something more along the lines of computer science and more technical programming.

There is a ton of value to a masters degree. You can learn a lot of things you wouldn’t be exposed to on a day to day job, you meet new people who are working in unique industries, and it can help bubble your resume to the top of a candidate list. A lot of senior and management roles have a minimum requirement of a masters degree, so you remove the feeling of rejection before you even start the application process.

Some of the best programmers I’ve worked with have no college background at all and have had great, fulfilling careers. There are plenty of great jobs not requiring a masters or PhD degree, but eventually you might become roadblocked from a job you really are interested in because you don’t meet the minimum education requirements.

I still believe the value of the work you do while you are working through a problem in a real scenario is better than a cherry picked problem in a university setting, but it does not diminish the fact there is a lot of value to the diploma you receive. Take the time to really understand the career you want to have before taking the next step. It took me some time for me to be convinced I wanted a long term career in data science, but doing so helped me be more focused and enthusiastic about getting my masters degree rather than feeling like it was just checking another box.