Can I switch from Sales to Data Science/Analysis with no degree in a year?

Question

I've been working for 5 years doing remote sales (from South America, for USA based companies) and want a career switch.

I read and watched a couple of videos that summarized the components of Data Science into: Coding Machine Learning algorithms for cleaning and processing of data coupled with the use of advanced math like linear algebra and statistics for visualization of the final product --please correct me if I'm wrong.

I was interested in learning all its components separately on my own (coding, math, AI) and when I found out there's a job where you use them all in one place, it really caught my eye.

The question is, do you guys think it's probable I can get a remote Data Science/Analysis job self-studying in a year or less? I wanna be completely sure before making such an important decision, since I'd be spending a lot of time learning every day for at least a year and don't wanna risk wasting it.

Answer 1

In my opinion, your career switch would be much more likely to work out if you enrol in some school to get an official diploma:

• The contents of the teaching would be more structured, you're less likely to have gaps in your knowledge.
• You're not alone to learn, so more motivation, possible discussion with teachers and students. Self-study is harder.
• But more importantly, at the end you get a diploma that is much more likely to get you a job: without it, it's going to be much hard to convince companies that you can do the job.

I agree that it's possible to learn on your own (assuming a strong motivation), and you might even be able to get a job eventually, but you'd need luck and it would likely take much longer... I think it would be a bit like gambling, whereas getting a diploma is a sound investment.

Answer 2

Be very careful: You are going to compete with a lot of people who have more than one year self education in a field that is saturated at the moment.

And don't underestimate maths. Watching a YouTube video is an appetizer. Not more, not less. The deep knowledge you need to truly understand what's going on is a lot, if you don't have the basics of calculus, statistics and linear algebra.

Programming and it stuff is also necessary, for example setting up a database. Hard to learn, in my opinion only by doing and time.

The "light" data science stuff will be more and more done with ai tools. The Bootcamps etc. certificates probably don't land jobs anymore. Toy projects also don't really help anymore to convince someone to pay you. The millionth MINST classification does only demonstrate, that you are able to use a search engine.

I don't say that it is impossible. It will just be very hard and one year is a very short time. And then it is even harder to find a job.

Answer 3

I wanna be completely sure before making such an important decision, since I'd be spending a lot of time learning every day for at least a year and don't wanna risk wasting it

It's a gamble.

Here are a few things that could go wrong:

• You might not cover relevant topics, or learn them in enough detail
• You might find it hard to cover the topics as quickly as you'd like (everyone is different)
• Employers will find it hard to tell if you have covered relevant topics in enough detail (a degree is an easy tick box, whereas understanding the scope of a DIY tuition is not)
• South America might not be a good place to get that kind of job (I have no idea!)

Learning a sufficient amount within a year of self study and convincing someone to give you a job is.... possible. Most people would take longer than that and plenty would never get there.

A degree is less of a gamble, but still a gamble.

Here are some things which you should do regardless of the route you decide to take.

1. Find some local people that do the kind of job you want to do. They can offer direction, give you an idea what the job market looks like, and might be able to open some doors for you further down the line.
2. Learn some programming or some theory in your spare time. This can be tough but if you can't bring yourself to do it in your spare time are you sure you want to make a career out of it?
3. Build programs. Solve exercises on paper. The biggest mistake you can make is to "learn" theory by reading and not putting it into practice. Solving problems is hard and is required if you want to genuinely understand the theory.
4. Build a portfolio. Make it visual. Showing someone that you built something is much more impressive than telling someone that in theory you could maybe build something.
5. Try to leverage the skills you've built in your current career. They shouldn't be front and center of a job application but you should point out all the skills and experience you can bring to a job that other candidates might not have.

Answer 4

You already have pretty good answers to your question but 5 years ago I was in a similar situation as yours so maybe what I learnt and noticed can be of interest to you and some other people. My situation was similar but different, compared to you I had some advantages (it was several years ago! + background in engineering and long-time self-taught programming skills) and some disadvantages (age, ...) so take what I write with a grain of salt, as just one example that may not apply to your personal situation.

5 years ago, I made a lot of research about Data Science and I arrived to the conclusion that the market will be soon saturated and that because of my unusual profile it would be extremly difficult to find a job as a junior Data Scientist. Nonetheless I decided to take the risk and I am very glad that I made the switch but the journey was much more difficult than I had imagined.

In 2025, it doesn't seem to be an easy time to look for a junior job in Data. In 2015 it was, according to what I have been told but for the past few years Data Science and GenAI became so popular that many "schools" and "training institutes" appeared (good business!) and trained a lot of students. Now there are many very smart people from all over the world in the field, which also explains all these amazing advances that appear so frequently in AI.

But as another consequence, the market is saturated with junior profiles, at least in my geographic zone. It may not be the case where you live so I suggest that you try the free 1 month premium offer at LinkedIn. Like that you will be able to see how many persons answer the job offers that you are interested in. For example, where I live, after one week companies looking for a Data Scientist receive often around 400 CV ! Last month I read a post on LinkedIn from a junior Data Analyst who had sent 800+ CVs and was still unemployed.

Also with LinkedIn, you will be able to "network" with Data professionals in your country who will be able to give you useful advice and market knowledge. You wrote that you want to work remotely but many people from all around the world want to so I don't think that it is very realistic for now. Moreover it doesn't seem that there are many remote positions for a junior profile.

That's why I asked you for your motivation in the comments. You will need passion and hard work to go over all the challenges that will appear on the way. Talent will help obviously. On the other side, money and wanting to work in a "cool" industry would not be enough motivation. Then luck is also a factor but one has to help one's luck and by definition it is not very reliable!

Maybe you could try to study while you keep your job. For me, discovering Deep Learning was so fascinating that for more than 1 year I kept working at my job, but I would get up 1 hour earlier everyday to read ML/DL books/websites. Often a good part of my week-ends and sometimes holidays was dedicated to study and practice Data Science. You could also enter some online competitions like Kaggle to learn faster and test yourself but it is not what will land you a job (though again I heard that some people got lucky).

Meanwhile if I were you, I would look now for a job in Sales (as it is your expertise today) in an AI company or a big company with Data professionnals working there (could be in any field). And in your country/city would be much better (even if the pay is less). Like that you will be able to meet local people working in Data and they will give you realistic advice tailored to your personal situation.

About education
Of course, don't believe all the ads implying that after a 3 months bootcamp (or even one year) you will find a job in Data starting from scratch. It is not going to happen for 99.9% of people. There is way too much competition in the field now and the subjects to master are quite numerous and often not so easy to grasp.
Clearly a "real" education in a university/school would be much better on your CV than an online "school" but it will take more time. Moreover, again think networking (in real life).
This said, professional experience is much more important to recruiters than where you got your degree from. So if you take this path, whatever you choose, make sure that you will be able to work many months (hopefully a total of 1+ year) and preferably in different companies thanks to internships or apprenticeships.
Personal projects are good but everybody have several of them. It will probably be a subject of discussion during a technical interview but it is very difficult to get one as a junior and the 1st screen will be on your CV and specially on your professional experience, even for a junior position! It is much easier for the ATS (automatic screening) and the recruiters (who naturally most of the time are not trained in Data) to count the number of years of professional experience than to guess how good is an applicant for a given job. Even more so, when they have hundreds of CV to go through.

Data Scientist or Data Analyst ?
You don't seem sure so first, research precisely the differences between the different jobs in Data. What would you prefer ? Unfortunately, the job market doesn't care much about what we prefer ;-) As you don't have an engineering/math/programming background, my guess is that your best chance (though not easy) would be to target a Data Analyst job. If you really want to become a Data Scientist, after a couple of years as a Data Analyst, the switch could be possible I guess (easier in the same company) even by studying Data Science by yourself on your free time.
Also in my country, most companies will ask for a 5 years degree for a Data Scientist position and it seems to be sometimes less for Data Analysts. Nonetheless the market for junior Data Analysts looks (I may be wrong) even more crowded than the market for junior Data Scientists.

Another option ?
If you are happy with your current job, life and "forecasted" future, another option could be to keep your job and learn Data on your free time as a hobby. And as I wrote above, you have the advantage to probably be able to find a job in many industries so why not do Sales for a company which has a Data department, network there, keep learning and practicing, ... who knows what could happen after a few years ?

Answer 5

Yes, switching in a year is totally possible, but it really depends on how much time you can dedicate and how you approach your learning. The good news is that you already have experience in sales, and that’s actually a big advantage. Understanding the business side and being able to communicate insights is something that many highly technical data scientists struggle with.

Now, on the technical side, you’ll definitely need to learn things like Python, SQL, and statistics. But don’t stress about learning everything at once—focus on solving real problems. Get into Kaggle, play around with datasets that interest you, build projects, and upload them to GitHub. Watching courses is fine, but actually practicing with real-world data is what will make the difference.

As for getting a job without a degree, the reality is that some companies require one, but many others care more about what you can actually do. If you build a solid portfolio and can prove your skills, you’ll have good chances. You might not land a Data Scientist role right away, but starting as a Data Analyst can be a great way in.

The most important thing is that if you genuinely enjoy it, you’re not wasting your time. Just be ready to feel lost at times—that’s normal. The key is to keep making progress and not compare yourself to people who have been doing this for years. If you stick with it, you could be job-ready in a year. Go for it