How does everyone in this bowl feel towards master’s degrees in data science/analytics? I didn’t study this in undergrad so I’m looking to get an analytics degree but I’ve heard mixed reviews.

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Not great. If you’re going to get a Master’s get an MS in applied statistics or CS. They are more rigorous and will help you be competitive for the best paying data jobs, which are research-based

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Echo what's said above. Disappointed with the rigor with most of the analytics programs. Most of our team is from engineering/stats/science backgrounds. (I'm a ML practitioner in big tech)

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While compsci and statistics are where a lot of the original data science folks hail from, industrial engineering / ops research is another. I’ve got a masters in that and it’s how I got started.
Note, I’m what I call an applied data scientist. I don’t build new algorithms or anything cutting edge like that, I help companies actually use their data. My programming and linear algebra skills aren’t what they used to be because they don’t need to be.

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Yes

Pick what's right for you. My MSBA was mostly math from an econometrics perspective, skipping just a few of the proofs and swapping econ theory the quant econ cohort had for more life-relevant classes (that yes, probably could've been replaced by several years experience naturally). I'm glad I did these "side" classes though, since it fast forwarded my career more than a few years.

Would an extra class on longitudinal methods or survival models have been more valuable in the long run than getting a jump on easy stuff like data viz or marketing analytics? I couldn't tell ya, but I can say that I feel plenty equipped to read about these topics on my own now as needed. To give you an idea on the statistics we did cover, the first quant class was taught from the canon Casella and Berger book, which just about every quant program uses including pure math PhD programs. My favorite class was the decision science one in the last quarter, which did a wide sweep of "good to know" applied techniques with derivations and papers. Worked on everything from Bayesian prediction intervals to copulas. I still remember the very first exercise, it was a trick question to do what looked like a straightforward hypothesis test. From some data, almost the whole class concluded that a lethally poisoned well was safe to drink from 😅

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I did one and got asked to join an internal DS team halfway. Lots of my work ideas were inspired by classroom learning because my program tries to teach you how to think, not just how to apply algorithms.

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