Hey everyone, I have been trying to break into the data science world as a strategy consultant. Have put in numerous hours after work and on weekends to learn programming/ DS and algorithms, ML, and statistics. I now have a pretty good resume of personal projects, but am having trouble getting any interviews. Should I go get an MS or keep on trying to find a job as a data scientist? Thank you for the advice.

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Keep applying don’t jump to an MS unless you have to. I would recommend focusing on roles where you have domain expertise. Also lots of data science roles don’t have data scientist in the job title.

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Thank you both for the detailed a advice. It was very helpful and I plan to implement everything. (Just downloaded goodfellows for the second time I will pair this with some more digestible coursera courses lol).

Following. Quick tip: nonselective online degree programs, especially from no-name schools, are not worth the money.

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I was in the same boat, then I did Georgia Tech OMSCS and it helped me pivot.

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Do a masters to learn, not just get a job. If you're happy with you level of knowledge and the roles that maps to, which of these makes more sense? - the time and cost of a masters -no additional cost applying places continuously and networking for half that time The latter, by a very wide margin. Of course, you do have to know enough... You won't regret a masters, but it's not an efficient use of time if you're a self-study powerhouse that can independently study graduate statistics. Quick check and not entirely uncommon interview question: derive OLS (matrix notation) and explain as you go. If you were comfortable with this at some point in your self study and can relearn it easily, you're probably on the right track even without a masters. If not, you'd benefit from the MS for learning. Btw, it's not that the regression derivation is something special--just a good check for how deep you've been diving up until now. And there are certainly positions that don't require this level of knowledge.

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