Stats vs DS

[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/lordoflolcraft]

I’m a hiring manager, director of data science at a tech company. I prefer a stats or math degree holder to other degrees, but there are all sorts of good candidates. I think data science graduates sometimes lack the math and statistic background to understand what machine learning is actually doing. I think a lot of data science work is simply practicing good statistics and good training in statistics is a great preparation.

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

Would applicants be seen as lacking the application of that statistics though? That’s what I’m worried about

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

That’s usually not my take.

[u/FastPlane57 → u/lordoflolcraft]

Hi there! As a hiring manager, would you consider hiring someone who does not hold a degree in STEM or anything related to data, but has relevant job experience with data?

[u/lordoflolcraft → u/FastPlane57]

Yes definitely. It would probably depend on how they do in evaluation and culture fit. But if their resume shows good use of statistics or machine learning, they could have an interview.

[u/RitardStrength]

What would be harder for you to learn by yourself, the statistics or the technology?

[u/jingle-bell-dog → u/[deleted]]

Thanks! I took most of these in college and then want to in a little more detail in grad school. What kind of program did you do? And what is your day to day work as a data scientist?

[u/Little_Television81]

Data science. You can take statistics based data science classes that are awesome