6
$\begingroup$

I'm going to do an undergraduate degree next year. Data Science major is there but I was wondering if a statistics major with a minor in data science would be more valuable? Which degree would be more in demand?

I am also planning on doing as many internships as possible to gain practical skills and experience. I am also contemplating the value of a masters degree, and whether it is worth the time and money, or if an undergrad+internships will suffice. I already know Python and I will learn R and SQL as well. Whether this is in university or otherwise (or both).

I will want to specialise in data analysis using statistical analysis paired with artificial intelligence.

EDIT: I’m in Australia and looking to go to the University of Melbourne (I’m pretty sure its #1 in Australia for computer science and math/statistics)

$\endgroup$
  • 2
    $\begingroup$ I'd edit as to which country are you from; it's different everywhere. $\endgroup$ – Itamar Mushkin Jul 6 at 7:13
  • $\begingroup$ Note that this question is highly based on opinions and not in facts. Also the field is changing and no one knows what will happen in a few years $\endgroup$ – Carlos Mougan Jul 6 at 19:27
10
$\begingroup$

If you can manage it, I suggest focusing more on Statistics. Statistics can be a demanding field, and takes a lot of effort to attain a degree. Of course, a Data Scientist also needs several skills besides Statistics, such as Software, Data Engineering and Visualization, but Statistics knowledge/skills are the most rare to find, and therefore can be the most valuable.

I worked the last 8 years in a data science department and found that when looking to hire a data scientist, it was often difficult to find someone with a solid statistical background. Most candidates had software, engineering, data and visualization skills. However, someone with a stronger statistics background would be hired over the other applicants, and usually with a higher salary.

Internships are very valuable, they will help you get your foot in the door before you graduate. Some companies may even offer you a job during your internship if they like your work. Some of the bigger companies will pay for your continuing education as they will get a better employee. It is a good investment for both you and them.

A Master's degree will also be beneficial, but may limit your chances to get a lower paying entry level job. Larger companies will usually prefer a Master's over a Bachelor's degree.

Response to your followup question:

  • I strongly suggest doing the internships, they can dramatically improve your chances to get a job when you graduate, especially with the companies you did the internship with.
  • The choice between Masters with little experience vs Bachelors with several internships would be much more difficult to make. Overall, the better choice would be to get the Masters degree with a few internships along the way.
  • Also, I suggest going with Statistics all the way, Bachelors and Masters. Several of the topics in Data Science will evolve over the 6+ years it takes to get the Masters, but the underlying Statistics will change very little.
  • Maybe get a minor degree in Data Science or a Statistics degree with an emphasis in Data Science.
  • You can also consider looking for a job in between the Bachelors degree and Masters, and if you find a good job, you can always get your Masters degree while you are working and earning money.
| improve this answer | |
$\endgroup$
  • 2
    $\begingroup$ I'd second that. Also consider this: At university you will have lots of time to spend on properly understanding complex concepts (Probability theory, Statistics, Learning Theory, Algebra,...). IMHO learning the application side of Data Science (product, databases, coding) can be done either on the side or during internships much easier than the other way around. $\endgroup$ – Simon Boehm Jul 5 at 16:14
  • $\begingroup$ Thanks for this, however I still have a couple of questions. How much more in demand would a masters degree with limited experience be over a bachelors+internships. And for a masters degree, would you suggest a data science masters over a statistics one, assuming that I do a statistics bachelors? Thanks. $\endgroup$ – Simplex1 Jul 6 at 2:14
  • $\begingroup$ @Simplex1, my response to your followup questions are included in my answer above. They wouldn't fit in a comment. $\endgroup$ – Donald S Jul 6 at 3:01
  • 1
    $\begingroup$ @Simplex1 You’re years away from having to decide on the subject of your master’s degree. If you study statistics in detail like you would with a bachelor’s in statistics, you’ll have a solid idea of what to look for in a master’s program. You’ll be able to gauge the quality and content of individual data science programs. $\endgroup$ – Dave Jul 6 at 3:04
  • $\begingroup$ @DonaldS Thank you very much for the detailed response. $\endgroup$ – Simplex1 Jul 6 at 3:09
3
$\begingroup$

Think about the future. Software development.

Even though now you can get away with average programming skills in the future more and more of what now is machine learning and data science will be abstracted away and accessible via simple API calls. Take a look for example at FastAI almost everything is abstracted away and even tough pytorch is underneath you do not even need to know to achieve good results. Of course experts will be always needed but his will be a minority. Data science will be a simple tool kit in a software engineers knowledge base.

Reference: Mathematician working as a machine learning engineer.

| improve this answer | |
$\endgroup$
1
$\begingroup$

Bachelor of Information Technology.

Speaking as an Australian whose Bachelor degree involved programming but wasn't labelled "Information Technology", I would strongly recommend getting an IT degree if you want to work in IT (which Data Science would be classified as). I've spent multiple years trying to find work in IT with no success, which is why I've gone back to university to get a Masters Degree that actually says "IT" in its name.

| improve this answer | |
$\endgroup$
  • $\begingroup$ I'd say Data Science is distinct enough from "IT" (or a distinct enough subset) for general advice related to IT to not really be applicable. $\endgroup$ – NotThatGuy Jul 6 at 15:38

Not the answer you're looking for? Browse other questions tagged or ask your own question.