I have an advanced degree in a field, which is only to some - limited - extent quantitative. I've learnt a bit of programming on my own and have had an opportunity to use it professionally already, although this was never my main task during my jobs so far - more of a "side gig" within my job when we needed to understand something better and I had a few hours to spend playing with data.

Now I've landed a job in advanced analytics, as a senior specialist (I'm surprised myself how easy this resulted to be).

As this would be my first job in analytics/ data science - a kind of a career change, I'm curious whether this make sense.

I rule out studying again. But I would need to learn really a lot "on the job".

How probable is it that the lack of a degree in maths/ physics/ IT/ data science would be held against me if I accepted the position and I wanted to switch from it to another job in 2-4 years?

Is it one of these jobs where you meet people from different walks of life (like marketing), or something where a lack of a quantitative degree disqualifies you and makes it impossible to have a good career?

I'm wondering to what extent the company that has just sent the offer is an exception here.


It depends, but generally, if it's "BI", or "Analytics", you'll find plenty of companies that don't insist on a relevant degree (even if the job post says "degree in xxx preferred" or even "required", in many cases it will be fine if you have relevant experience).

When it comes to Data Scientist or Machine Learning Engineer, it can more frequently be an issue. Some companies do have a strict policy of not hiring Data Scientists without a relevant PhD/Masters degree.

I'd say if you can acquire the necessary skills and accumulate great experience, you can have a great career without a relevant degree - at least in the current economic climate. Many companies are desperate to hire data talents that they are turning every rock, so to say. If your experience is good, lack of degree won't be an issue for a lot of companies.


Sometimes, companies are more interested in experience rather than degrees.

If you take the job you will start earning experience on the field, which would help you transition in the future if you decide to change to another company in the field.

You already landed the job, so that means the company sees potential in you despite not having a degree on the specific field.

Now, you should focus your efforts to do your (future) job the best you can, and learn the most out of it. This will make it easier for you to show your experience on the subject and switch to another related job in the future if you want so.


Setting aside the question of whether or not you have a particular degree, I think you need to ask yourself honestly whether or not you have the skills, knowledge and capabilities to do what will be required of the job. After all, that is what really matters, not whether or not you have a particular degree.

It seems to me that the fact that you don't seem to know what the job will entail is not a good sign. Perhaps you should consider firstly doing some more research into the details of what the job is and what will be expected of you, before you make a decision?

I'm not sure if it would be a great career move to accept a position where you are totally out of your depth and completely unqualified. Again, I think only the background research would tell you this - do you know anybody that has a similar position that you can get some advice from?

  • I know very exactly what the job will entail. Not sure why you think I don't. – master_of_disaster Nov 15 '18 at 18:27
  • @master_of_disaster I inferred that from your statement that it would be your first job in analytics/data science, and the 2nd-last para where you asked "Is it one of those jobs ...". Suggested to me that you didn't know a lot about the position, but I perhaps I misinterpreted your question. If you know what it entails and you are confident you can do the work, then I would agree with DarkCygnus - go for it. (in that case I'll probably delete this answer). – Time4Tea Nov 15 '18 at 18:31

Short answer: you probably don't need the degree for most jobs. As is usually the case with these answers, being conversant with the topic at a professional level, having a portfolio of high-quality work, and (to a lesser extent) having certifications can probably deliver the most of the same information that holding a degree would. There is some variation by field as well-- a smidge of technical "data analytic" knowledge complemented by other knowledge is sometimes ideal (I work in health care analytics, and clinical experience is an absolutely huge advantage to have when poring over reams of data).

However, even if you are capable of doing the job, it may be a mistake to assume that your skills are equivalent to those that you would have if you had the degree. It sounds to me like you're open to always sharpening your skills, which is awesome. If you want to move into analytics for your career, make sure to retain that attitude and constantly watch out for arrogance. It's extremely easy to wind up in a situation where you perceive your understanding to be more complete than it is (it's a constant issue for me, and I both work in this field and also have the quantitative-skill-degree background). There is just a huge amount of information to know.

Anyways, my advice is to focus far, far less on titles and qualifications and more on the work. What you're called on your business card is mostly unimportant. What you can do with data of the type your employer has, and on the scale that they have it, is supremely important. You will probably be a great fit for many roles in this space, and a terrible fit for many roles as well.

"Analytics" is deep in buzzword territory at the moment, and so you can probably sell yourself successfully without the degree. That also causes a few difficulties for you:

  1. There is no way of knowing in advance how much the person you report to understands the subject matter. This is double-edged-- a superior who doesn't know enough to catch you out in something that "everyone" with a related degree would know won't catch you being "underqualified", but they also won't be able to correct you when you err or teach you more.

  2. A lot of people who want work products that would fit well under "analytics" don't really understand what they want, how to use what they want if they were to get it, and, crucially, what limitations exist on what can be known/done with what they want. This is, in my opinion, the area in which formal education is the most useful-- you would have that background knowledge to add. It's always hard to estimate what you don't know, but that risk can be a lot more acute when you are mostly self-taught.

  3. There are a ton of people with positions and titles like this, with huge variation in quality among them. Some people are awesome at throwing together reports in PowerBI or Tableau, but understand essentially nothing about the underlying concepts and so are likely to make lots of errors, sometimes very consequential ones, outside of routine work planned and supervised by more knowledgeable people. The risk of this varies with specific responsibilities associated with specific jobs (i.e., if data visualization is your assigned role, it may not matter that you don't understand intricate details of logit regressions; the converse can also be true).

  4. "On the job" training works well for some areas and some people, and very poorly for others. You can pick up a lot of SQL coding skill while working, because you can often test your queries at intermediate stages and validate against fixed, external information. That's less the case when you're relying on a 3rd party library to run elastic net regressions (learning all of the underlying concepts from scratch is probably not what you were hired to do on the clock).

  5. A quantitative-field-focused degree suggests a lot about what skills you have, and what knowledge you can tap. A CV entry listing "data analyst" does not. It's just too broad of a title for every job featuring it to be directly comparable.

On the other hand, there are plenty of people with applicable degrees that have middling applicable skills at best. You are extremely unlikely to be anywhere near the least competent person making a living doing this sort of work.

  • Upvoting especially for the second and last paragraphs, but there are some very valuable insights throughout. Good answer. – Kilisi Nov 15 '18 at 22:59
  • "Your statement that you found the work immediately easy sets off all sorts of sirens in my head". What a strange comment. I wrote I found landing a job in analytics much easier than I expected. Which is true. I applied in several areas - I had experience in all apart from analytics - but both my response rate and job offer rate in analytics/ data science was several times the rate I got while applying in less quantitative fields in which I actually have work experience. I find it quite disturbing how people misread posts on here and are judgemental about what they misunderstand. – master_of_disaster Nov 16 '18 at 2:43
  • @master_of_disaster I will edit my answer accordingly. It's a relatively easy misreading, I think. However, given my original understanding of the comment I'll stand by the alarm bells. Because of how vague "analytics" is as a description of the work, finding it easy despite little relevant training suggests that a person is one of: (1) a person with inherent talent for the work (awesome! but rare), (2) on the "softer side" of analytics (data visualization benefits from, but does not require, the same quantitative skills as other work in the same field), or (3) in Duning-Kruger territory. – Upper_Case Nov 16 '18 at 15:20
  • (continued) That you feel disturbed is unfortunate, and I hope that you will accept that that section of my answer was an honest extension of my mistake. I would not be more impressed to hear that an amateur data analyst found the work easy than I would be to hear that an amateur surgeon found heart surgery easy. It's not impossible that the necessary talent for finding the work easy is there, but it's a lot more likely that the amateur surgeon is mistaken about how good they are at the task. – Upper_Case Nov 16 '18 at 15:25

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