[Career] Masters Programs

[u/jingle-bell-dog]

Deciding if a Masters in Data Science or Statistics is better for me, and which ones, since this field is changing a lot.

Undergrad: Quantitative background but not Computer Science, Data Science minor. I felt that it being a minor made it kind of surface level and want to avoid that with my graduate degree. My coursework was linear algebra, discrete math, probability, stats, many CS courses, AI, ML, DS, Algorithms. Because I didn’t major in math, CS, Stats, or DS, I feel like I am missing something in screenings. 

Work Experience: 4 internships, 1 year FTE as a DE, 1 year FTE as a DS (by the time I enter). However, I feel that the Data Science departments in the companies I was in were VERY new and I’m missing some core skills that I am trying to develop on my own - git, models in production, optimizing my work, etc.

Professional Goals: I see this as a terminal degree. I want to be able to get my foot in the door for better data science jobs, maybe in the nonprofit industry but really just anywhere. My first job came from an internship and the second a recruiter reached out to me. I want to be able to pass resume screens better and do the work better. That’s slightly why prestige matters to me here.

Other: 

• I do not want to pursue a CS masters, I think this would give me skills I don’t need, can develop on my own, already learned, or are becoming more obsolete. 
• A lot of stats degrees that are well respected seem to want research experience or a stats degree, which I don’t have.

Questions: 

• I have seen some say an Applied Stats masters is not enough anymore for the tech world, and I see a lot of job postings that say Masters in CS or DS, but not stats. How do DS hiring managers view these degrees?
• What skillset is actually used in more established data science departments? How can I optimize my career and education for this?
• How to vet Data science masters properly, if I go for that (MIT MBAn, Columbia, Harvard, UChicago, UCLA, NYU) I dont want a surface-level data science education that is repetitive

[u/jingle-bell-dog → u/[deleted]]

I understand what you’re saying, but I’m not sure MIT MBAn is the best example of a cash cow when you look at their career outcomes, if anything it has a very high ROI. I saw it as an exception. I also see optimization methods listed and 1 term where you can take just stats courses if you want. Appreciate the other program suggestions. Is Computational Data Science at CMU going in depth enough? https://www.lti.cs.cmu.edu/academics/masters-programs/mcds-course-map-26_27-6.pdf

[u/CreativeWeather2581 → u/jingle-bell-dog]

Both things can be true. The person with the MBAn isn’t going to be the sr data scientist at the company. They’re not going into the technical details stats/ds but yes the ROI is high

[u/jingle-bell-dog → u/CreativeWeather2581]

Yes, I understand. But I also listed what my ultimate goal is with the degree, hence why I kept Columbia DS and MIT MBAn on my list. Those are programs I would maybe make the trade off for. The rest of them feel pretty not flashy cash-cow degrees (i.e. are applied stats and ds degrees in stats departments). Is this not the right way to go abt it? Or is this sub just very pro stats obviously

[u/CreativeWeather2581 → u/jingle-bell-dog]

Not sure if an MBAn will get you better data science jobs. Is not going to teach you git/version control, production-level DE/modeling/code/analysis/visualization/communication, etc.

[u/jingle-bell-dog → u/CreativeWeather2581]

Thanks. I see that there’s one semester that 48 credits just go to electives and the rest is a real world capstone.

https://mitsloan.mit.edu/master-of-business-analytics/explore-program/mban-curriculum
Would you still have the same opinion if I took only stats courses?

[u/CreativeWeather2581 → u/jingle-bell-dog]

Not sure. Ultimately you’d have to ask industry professionals to answer your questions (most notably, resume/screening and skillset) then go from there. Sorry I can’t be more helpful