StatsG0d

I don't see what grades you received in Calculus I-III, which are important. Your B in linear algebra will certainly raise a few eyebrows. The worst thing so far is your GRE score. You're going to have to do markedly better (like V: 150+ and Q: 165+). However, none of the programs you listed are highly known in statistics, so it's definitely possible you get in to any of those programs provided your GRE score is much higher. With a good grade in Analysis and a good GRE score, I think you could aim higher.

You have a pretty deep math background and a really high GPA. Your letters sound reasonably strong. I think you have a really good chance at a top-20 stats program and a top-5 biostats program.

I second this. I don't think any of these programs will help you get into a PhD in any field, including data science. Moreover, I believe there's really only one "PhD in Data Science" degree, which is at NYU. Their course requirements, are vague, but this is from their admissions requriements: The Committee welcomes applications from candidates with relevant undergraduate/master’s degrees and candidates with work or research experience in data science. Relevant degrees include mathematics, statistics, computer science, engineering, and other scientific disciplines that develop skills in drawing inferences or making predictions using data. Coursework or equivalent experience in calculus, probability,statistics and programming are required. If you're interested in statistics / computer science, you will be much better off taking the courses required for admission for those programs. For the former, the minimum is Calc I-III, Linear Algebra, and Real Analysis I. It's getting more competitive, and many successful applicants have gone further (Real Analysis II, Abstract Algebra, Complex Analysis).

If the OP doesn't want to attend a program they already committed to it's not really an issue. I'm sure it's not that rare. The issue is that the OP wants to attend a different program. The way I see it, there are only four options: 1.) Ask the other programs if they would consider re-admitting you. If so, you can speak with your current program and rescind your offer. I think this is a long shot because funding is already probably pretty tight with COVID and we are over a month past the April 15 deadline. My .02 about this is that it's a very bad look, and I certainly wouldn't do it. 2.) Enter your current program and try to leave after one year. As others have mentioned, this is difficult because it might raise eyebrows--why would a student leave a program without a master's? Moreover, it could be awkward to ask for letters from the current program. 3.) Enter your current program and leave with a master's degree. Sure, you will have wasted a year. But it's not the end of the world and at least you have something to show for it. 4.) Enter your current program and just finish the entire degree there. This is the easiest option. As I and @Stat Postdoc Soon Faculty have said, it might be helpful if the OP explains why they are having second thoughts. When people transfer programs, it's usually because they could not connect with the culture or they have research interests that do not align with the faculty. I have not heard of anyone wanting to transfer before they arrive. For all you know, you could end up loving the department you attend.

At this point in the admissions process, I highly doubt any of the school that you have already turned down would re-admit you because they have already admitted waitlisted students who would have taken your spot. One strategy would be to tell your current department that you can't come anymore for some reason and apply to other departments next year, but this could be risky as there's no guarantee you'll be accepted again. With recessions, more people become interested in graduate programs as they lose their jobs, so the competition could be much more fierce. Why are you having second thoughts before joining the program?

That's a great question. My guess would be that programs that have their PhD qualifying exams after their second year would be more willing to accept master's students, probably because they would want you to take the core PhD classes in the department. You could try emailing some of the graduate coordinators at the departments. In my experience, most of the time they are pretty receptive to emails. Worst case scenario, they ignore it and forget about it.

I know someone who left a top-30 statistics program with a master's and ended up getting into a top-5 biostatistics program. That said, they were rejected everywhere else. I think it depends on whether the department you're applying to prefers master's applicants or not--some programs want students right from the beginning, others are willing to accept advanced students.

The only one I am aware of is University of Illinois

I think you could aim a little higher than what @Stat Postdoc Soon Faculty says. My profile was weaker than yours, and I got into all the schools they mentioned.

It will help your application for sure, but not as much as taking the classes. Analysis is a prerequisite for most PhD programs. If it's not officially a prerequisite, it's highly recommended. Given that you are an international student, you will face stiff competition from other international students who have taken Analysis. You don't want to preclude yourself from consideration by not having the minimum background. If you're interested in machine learning and AI and you don't want to take the math courses, perhaps you should consider a CS program.

This is crazy. In general, it's a good idea to apply to a wide range of schools, but I am still surprised you did not get accepted to at least one of these programs. Next time, try applying to a wider range.

I agree with @bayessays. The only thing that could potentially boost your profile would be to get a master's degree in probably mathematics taking some hard courses (e.g., topology, abstract algebra) and excelling in them. I also do not see a real analysis course in your profile, which would bar you from admission from most PhD programs (regardless of your grades).

This is pretty tough and such a terrible situation. I guess if it were me, I would see if I could take out a student loan to pay the in-state tuition until you arrive in the US and TAMU can pay you the stipend in back pay. You'd have to pay back a little interest, but provided you could start in-person Spring 2021, it wouldn't be too bad. The issue with starting in Spring it would seem is that generally grad school classes depend on the previous semester's classes. So you would probably have to take all electives in Spring that have no prerequisites (if this is even possible). Pretty much all electives across stats departments require Casella Berger I and II, so I'm not sure what benefit there would be to starting in Spring.

I think Wager (Stanford) and Moodie (McGill) also work in this area.

Agree with @bayessays. Honestly, you could probably target more highly ranked schools.

Given the political, economic, and health environment, I was wondering if statistics / biostatistics students and postdocs on the academic job market could share some advice on how to weather the storm. I believe that I will be on the job market May 2021, and it is likely the situation will be very similar as today.

As always, @bayessays and @Stat Postdoc Soon Faculty gave some very good points and advice. I think many programs are starting to shy away from master's coursework -> PhD coursework -> electives. I believe PSU and TAMU are two such programs where the qualifying exam is taken after the first year, and the first year curriculum includes measure theoretic probability. If you have the requisite background, they might let you take the qualifying exam as soon as you arrive. Regarding UK programs (programmes?), based on LSE and UCL, it does not really seem like funding is the norm, whereas I feel like in the US, no funding is the exception.

I still think pedigree matters for industry jobs (although I wish that it did not). Professors from top departments have lots of industry connections and can easily help their students get jobs. Obviously, the better the program, the more industry connections there will be. Moreover, note that even students from lower ranked programs can get pretty good academic jobs if they work with good professors. For example, UF Stats is not a very highly ranked department, but their faculty is stacked and indeed they send their students to some great post docs (e.g., UPenn, Sloan Kettering) and recently even sent a student to a tenure track AP position at Minnesota Stats (although this is an outlier). TLDR: it's not necessarily true that pedigree matters for only academia and not for industry. The converse is also false. In general, it's easier to get a good job to attend a higher ranking school

That's fair, but IMO if you're at least 50 percent certain you might want to do a PhD, it's worth it to apply directly. Worst case scenario is you get rejected or an unfunded master's admit, but the upside is you get a funded offer and could honestly probably leave with an MS, even if you lose funding for the 2nd year, it's worthwhile. What math classes have you taken and what grades did you receive in them?

First, if you're keen on doing a PhD, I would suggest you apply to PhD programs outright. Many departments will consider your application for a master's degree if they do not think you're strong enough for a PhD. Moreover, I can't think of a department that does not allow you to get an MS en route to the PhD, as all the first year classes are generally the same. You might have a decent chance at a biostats program outside the top 10 or a stats program outside the top 25 (depending on the aspects of your profile). While the low GPA is concerning, your math-specific GPA will hold more weight, in addition to the breadth of math courses you've taken as well as standardized test scores and letters of recommendation, and reputation of school. A 3.1 looks differently depending on whether it came from, say, Duke, UNC, or ECU.

Pretty difficult situation here because you're comparing a very good biostats program with potentially no funding vs. a funded offer from an unknown program. If you're really determined to do a PhD, I would be tempted to stay at Minnesota for two reasons: (1) the pedigree of the school is better; and (2) it might look strange to the adcoms to see that you went from a prestigious program to a non-prestigious one. For (2), I guess you can indicate financial hardships on your personal statement, though it's unclear how much that will be taken into account, and I'm sure this varies heavily by department. I also think it might help if you posted your full profile (undergrad degree / gpa , etc. ) so that we can understand how strong of an applicant you are irrespective of the grad program.

Obviously, CMU's statistics / ML program would be a great fit. Other than that, I'm not sure there are many statistics programs that offer ML as foundational courses. Perhaps the best thing to do would be to target departments that have strong ML faculty and whose students take the qualifying exam after the first year. That way, you'll receive the foundational statistics knowledge you'll need without having to go super in depth on topics that won't relate to ML, and can get started taking ML electives earlier. Another thought is to look at the biostatistics departments that are doing some good research in ML / precision medicine. Washington (Shojaie), NCSU (Davidian, Laber), UNC (Kosorok, Zeng), McGill (Moodie) are some of the "heavy hitters" that come to mind that publish in top journals.

In most circumstances I feel like you can probably get funding by your second semester, but with the incoming recession, I certainly would not take the risk.

I suggest that you read this thread, particularly the posts by myself and @Stat Postdoc Soon Faculty. If you have further questions, I'm happy to weigh in.

I don't think jobs around where you work are relevant. Companies recruit PhDs nationwide, so being in Michigan / NC is not going to constrain you. I'll echo the others and say that the choice of UNC vs Michigan really boils down to whether you want to do genetics or not. I'd contend that Michigan is the best in the world at genetics. UNC offers everything, so you could do genetics there as well, but UNC is not as focused as Michigan.