How to Pick a Masters Program for a Career in Data Science
I started my career in marketing, which made sense after finishing my BA in Communication. Part of my job included analyzing data, which I enjoyed doing more than the other parts of my marketing work. Eventually, even though my analyst skills were very basic, I was moved into a Marketing Analytics role. Once I started to get exposed to tools like R and Power BI, I was fascinated by what you could do with more computing and mathematical knowledge, and I decided that I wanted to learn everything I could about working with data.
I decided that a masters degree would be the best route to “learn everything.” Plus, having that credential on my resume would potentially open more doors later in my career. I ended up enrolling in the MS in Data Science program at DePaul University in Chicago in 2018 and graduated in 2022. I continued to work full-time while taking classes part-time (1 class per quarter). I’m now working as a Product Analytics Data Scientist at a tech company.
There were a few things that factored into which program I chose, and more things I would consider now that I’m done. If you’re interested in getting a masters degree to support a career in Analytics or Data Science, here are my recommendations.
What Kind of Program Should You Do?
Before even picking a specific program, you should decide what type of program you want. This depends on what kind of career you want. If you’re not sure, check out this post outlining different types of data jobs.
Another thing to consider is what your skill gaps are. I had a very strong business background from my years in marketing, but I lacked almost all of the technical skills and statistical knowledge, so I wanted a program that was stronger in those areas.
There are a few options for graduate programs. The names aren’t always consistent, so definitely focus on the curriculum and what you’ll actually learn.
- Data Science. This is any program that is more computationally focused specifically on working with big data, usually, the emphasis is on ML or Machine Learning. Often the program is part of or overlaps with the Computer Science program/school. Expect to use Python and/or R in most or all classes (my program used both), and to learn various predictive and machine learning algorithms, including an overview of the math behind them. You’ll probably also cover topics like data visualization, distributed/cloud computing, and databases (including SQL). This type of program is ideal if you want a role as a Data Scientist who is focused on solving vague questions or problems with data and/or researching ML models to solve problems.
- Computer Science. Many Data Science programs are just a re-branding of their data/ML track within a Computer Science program, so getting a Computer Science degree is also a great option, especially if there is a Data Science or ML track that you can follow. These programs will be the most technically rigorous and are a good option if you want a role that is more software engineering focused, like a Data Engineer or ML Engineer or ML Ops.
- Statistics. These programs will obviously go much deeper into statistics and math and are ideal if you want a role as a Data Scientist who is focused on solving vague questions or problems with data and/or researching ML models to solve problems.
- Business Analytics. These programs are usually part of a university’s School of Business. The curriculum covers a mix of business classes and analytics. It may not get as deep into programming or math/stats. This program is ideal if you prefer a role as a Data Analyst or maybe in Business Intelligence, or something that isn’t specifically a data role but will use data. However, if your goal is a role in data science, machine learning, or data engineering, this type of program probably won’t be technical enough if you don’t already have a strong quantitative background from your undergraduate studies.
Should You Do an In-Person or Online Program?
When I enrolled in my program in 2018, there were very few DS/analytics masters programs available (at least compared to today), and most were either completely in-person or completely online. The one I ended up choosing was the only one (at the time) in my city that had the option to do both in-person and online. That was one of the main reasons I picked that program — I personally preferred to be in-person, but I liked that I would have the option for online if I needed more flexibility. Additionally, all of the classes were recorded and could be watched later by students in both the in-person and online sections. (This was pre-pandemic before many of us had even heard of Zoom.) This was a plus for me because I occasionally had to travel for work or work late, so I liked that I could still access the lectures even if I wasn’t able to attend in-person.
I originally planned to do all my classes in-person … which I did, until 2020, when we all had to go online due to the pandemic. Thankfully, because my program was already structured to support online students, it was a very easy transition. Eventually, we were able to go back in-person and I went back to in-person classes. But I got to experience the program both ways.
Personally, I still prefer in-person.
For one thing, it makes connecting with other students as well as the professor so much easier. A big benefit of graduate school is the networking, and I feel those opportunities are very limited if you are an online student.
The other reason is being in-person keeps me accountable. There is a set time and place for me to show up and listen to the lecture. When the curriculum is pre-recorded and I have to find my own time to do it from home, I find that I am much more easily distracted. If that is the case for you too, then consider an in-person program.
However, online programs offer much more flexibility. You aren’t limited to the universities near where you live, you can study at some of the most competitive and respected universities no matter your zip code. Additionally, if you have a lot of other demands on your time (work, family, etc), an online program can be better accommodated. And at the end of the day, the students who did my program 100% online still received the exact same degree that I did. And literally covered the exact same material, since we all watched the same lectures, whether it was live in-class or live on Zoom or watching the recording.
Who is Designing and Teaching the Courses?
When evaluating programs, I would look at who created the curriculum and is teaching the courses. Ideally, you want the majority of your professors to have PhDs in subjects like computer science or statistics.
Additionally, make sure the professors are accessible — are they actually employed by the university where you are getting your degree? Can you attend their (in-person or virtual) office hours?
I’ve seen some masters programs that weren’t actually designed and taught by that university’s professors, but rather were licensed through a program like edX. Does this matter? Honestly, I’m not sure, but my preference would be for a program that was actually designed by that university’s professors.
Can You Get “Real” Experience?
Another thing to look for is opportunities to get real experience.
Does the university have any relationships with local businesses and organizations? Are there opportunities to do internships and/or “real” data projects using real data from an organization and basically serving as a short-term consultant? Or can you support research projects with your professors and/or PhD candidates in your program?
This will give you great experience for your resume, which is especially important if you enrolled in your masters program before getting any real work experience.
How Rigorous is the Program?
One concern about all of these new Data Science/Analytics programs is that they aren’t rigorous. Statistics and Computer Science have been around much longer and have a good reputation for being rigorous and teaching the same topics regardless of the university. Some folks feel that Data Science programs are just “cash grabs” by universities and that the students coming out of the programs don’t meet the standards necessary for Data Science roles.
While it’s possible that there are some programs out there that aren’t as rigorous, I don’t feel this is the case for all programs. I would look for programs that are closely aligned or overlap with a school’s Computer Science and/or Statistics program.
Also, what are the prerequisites? For example, my program required (among other things) that you’ve taken college-level Calculus in order to enroll. On top of that, they had prerequisite courses in statistics, programming (Python), linear algebra, and more calculus. I would be suspicious of a program that didn’t require mathematical knowledge unless their curriculum covered it at the start. That would indicate to me that they are just teaching you how to run code without understanding it, which is not ideal.
I would also look at the length of the program — if you can get through it in less than a year, I would be concerned that the curriculum doesn't go deep enough to give you a solid understanding of the math behind what you’re learning. For comparison, full-time students need at least 7 academic quarters to get through the program that I did, which translates to 21 months from start to finish. If they need to take the prerequisites, that would be 8 academic quarters, which would take 24 months. (Since I was part-time, it took me twice as long — 48 months from start to finish.) And even with all of that, I feel like there are still more subjects I would have liked to cover during my masters program.
Will the Program Help You Achieve Your Goals?
Presumably, you have some kind of goal for what you want to do after you finish. If you don’t — then I don’t recommend enrolling in a masters program. Figure out your goal first before spending thousands of dollars and hours on a degree.
The best way to figure out if a specific program will help you achieve that goal — see what the alumni are doing. You should be able to find them on LinkedIn. Do they hold the type of job you want? Are they working in your target industry? If so, that’s a good sign that the program they did can help achieve that goal.
I also recommend reaching out to alumni of the program(s) you’re interested in to ask about their experiences and opinion of the program.
If you can’t find any alumni on LinkedIn, that’s not a good sign. Even if it’s because the program is so new that there are no alumni, I would look for a program that’s been around long enough that you can see the results in the alumni.
Do you have any other advice for picking a masters program? Let me know in the comments!
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