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Do you need a college degree to be a data analyst

6 min readView all articles
By John Pauler
Aug 18, 2020

How Important is a college Degree to a career in Analytics or Data Science?

This is a pretty common question from aspiring Analysts and Data Scientists who are trying to get a foothold and are figuring out how to launch a career.

The question comes in many flavors…

  • “How much do employers weigh your college degree?”
  • “I picked a non-Math major. Does this rule me out for Analytics work?”
  • “I don’t have a college degree. Can I substitute bootcamps and online training?”

How much does a college degree matter?

This is a case where the reality is different from what I would like it to be, and also from where I think things are headed in the future.

The fact is, most companies still want employees to have completed a college degree for Analytics and Data Science roles.

I’m not saying I agree with this. I’m not saying a college degree produces a good ROI. I’m not saying that college educated employees perform better in these roles than those without degrees. All I am saying is that it is a very real practice for employers to filter candidates based on degree completion. This is particularly true for larger companies and for more junior roles (startups have more flexibility, and no one thinks about your degree if you’ve been working for 10 years in similar functions).

Why do employers use the college degree as a common filter?

  • It’s easy to do. This is a “quick and dirty” way to separate candidates.
  • A college degree tells them you were able to gain admission, and stuck with the program.
  • They perceive it as “universal” or “standardized”, to some extent. They know what it means (or at least think they do within a range).
  • They don’t have a better way.

This can feel pretty unfair to people who do not hold a degree but may have great skills or otherwise have high potential, but have a harder time getting their start.

I agree. It stinks. And frankly, it is a suboptimal way to identify potential candidates. In many cases, it says more about the opportunities available than the talent possessed or skills acquired.

We are working on the problem, creating affordable, project-based courses to teach job-ready skills that are available to anyone with an internet connection. Personally, I believe the rising cost of higher education and the increasing access to great online programs will lead to very different hiring practices over the next 5 or 10 years. That’s not what this post is about though. We’re discussing what matters to employers today.

How do employers weigh institution reputation, degree programs, and performance?

Of course, employers love to see candidates from well-respected institutions, with relevant courses of study, who got perfect grades.

But how much do each of those things matter?

This is one where mileage may vary. Certain companies and even industries place an enormous importance on “having the right pedigree”, coming from the right institutions. Consulting is a great example of this. Most employees at top Consulting firms come from highly rated colleges. Startups? This is another story. In my experience, background matters a lot less. I even worked in one startup that had a “No Ivy League” policy, thinking the entitled grads were not the right fit for a roll up your sleeves startup environment. This startup prefered "no name" institutions because their graduates tended to have more to prove and work harder (at least that was our CEO's theory).

In my personal experience, the program of study is important for Analytics and Data Science roles, so I weigh it much more heavily than the name of the institution. When I see someone who studied math, statistics, economics, computer science, or another related field, I have a high degree of confidence that they will be “technical enough” and “quant enough” to pick up the critical triangle of math, technical, and business thinking.

Of course, a student making good marks is nice to see. This will definitely help, but if someone has poor marks and just leaves their GPA off the resume, potential employers may make some assumptions but probably won’t be slowed down much.

In general, employers are trying to assess how good you might be at the job. Sometimes they do this very fast, within 10 seconds of seeing your resume. Do everything you can to help them say “yes” to continuing to consider you. Showcase your relevant formal education, online training, technical skills, and especially projects that you can relate to their business. Use everything you’ve got!

If you studied the wrong subject, what can you do?

Studying the right subjects serves as a strong data point that you have both interest and aptitude in relevant fields. If you didn't study "the right stuff", don't despair. There are other ways to demonstrate interest and aptitude. If you have enrolled in any supplemental training in very related fields, this looks great. List them high on your resume. Create a ‘Analytics Skills’ section to talk about what you can do. Personally, I love self-starters and taking the initiative to learn job-relevant skills outside of a degree program is something I have always loved seeing in a candidate. This can be done in relatively short amount of time, can help you land the job, and can help you ramp up quickly when you

Remember that the main filter companies are applying is simply whether you have completed a degree at all. In many cases, once you clear that hurdle, studying the “wrong subject” will be fine, as long as something else stands out to show that you have relevant interests and experience to help the company.

If you don’t have a college degree, is all hope lost?

Not at all. But let’s be honest, you are going to have a MUCH harder time than someone who has completed a traditional degree program. Again, I’m not saying this is right or even a smart way to do things. I’m just telling you the reality - many employers will rule you out. You’re going to have to work harder to break into the Analytics world. But once you are in, and have a couple years of experience, it will get a lot easier. Here are some things you can do to try and break in…

Learn relevant technical skills. Focus on project-based learning. If you don’t have the “right background”, you can improve your position with some self-study. Look for online courses that are inexpensive and extremely relevant to what you want to do. Then when an opportunity arises, you will have some relevant project experience to talk about.

Aim for small companies. Larger companies will have more rigid hiring practices. Look for small shops where you know someone. See if there is anything you can do there. Even if they aren’t saying “we need an Analyst”, startups are famous for allowing you flexibility to expand your role. Show up, do the job you’re expected to do, and then just start doing an Analyst role. Find things in data that can help the business. You don’t have to wait for anyone’s blessing. Just be tactful about it.

Work your network. Think about everyone you know. Which people exist at the intersection between liking you a lot and having the ability to help you. Those are people you should talk to. Let them know what you’re trying to do. Ask them for advice.

Go to the right networking events. The best events for you will be Analytics-focused meetups. Startup-focused meetups are good too (again, they may be the most flexible with hiring). Talk to as many people as you can. Let them know what you’ve been studying and what you want to do. Listen to what they have to say.

Try freelancing. See if you can get some practical experience as a part-time consultant. You might be surprised to find that the barrier to entry is a lot lower for part-time work compared to full-time roles. Consulting work can be a good resume booster, and it could lead to a full-time position too.

Consider volunteering your help for free. This can be tough to stomach. Not everyone has the bandwidth to do it when you need another job to pay the bills. But this can be a way to get more hands on experience if you are having trouble finding any.

Like I said, if you want to break into this field and you don’t have a degree, it’s not going to be an easy road ahead. You will need to put in some thought and some serious effort, and it will still be challenging. If you’re willing to do it, you can succeed, and it really is a fantastically rewarding career path.

NOTE: A lot of the advice in this section applies when you’re trying to break in, even if you do have a degree.

Hopefully you can take away some valuable tips from this article. If there are other things you would like to hear more about, hit us up on LinkedIn. You can message us directly, or @ mention Maven anytime. We are always happy to hear from you.

Happy learning!

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Author

John Pauler

John brings over a decade of business intelligence experience to the Maven team, having worked with companies ranging from Fortune 500 to early stage startups. As a MySQL expert, he has played leadership roles across analytics, marketing, SaaS and product teams.

John brings over a decade of business intelligence experience to the Maven team, having worked with companies ranging from Fortune 500 to early stage startups. As a MySQL expert, he has played leadership roles across analytics, marketing, SaaS and product teams.

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