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Yeah I'll admit I know next to nothing about VCU. UF's program is housed in their public health school, but there is either very little or no interaction between the stats and biostats departments. Still, I think there are some reasonably strong faculty members in UF's biostats department. And at least the option exists to take classes at a strong stats department and maybe get co-advised.

I just went through the application process and applied to 5 (very risky!) schools. They were all of the sameish type (seriously, I straight up applied to all Big 10 schools).
I've found that there's no predicting what's a safety and what's a reach. At least, there's very little predicting. A lot depends on fit. Is there a professor whose research catches your eye? Reach out before applying! Get your name on his/her radar. That might get you in.
Scores and grades matter, but fit matters more. Research experience matters even more, and letters of recommendation may matter most. If you can say "I want to go here because this person does this research, and I like that research and here's proof I've done that from my SOP and my profs' letters of rec" you'll be a lot more appealing than someone who says "I want to go here because this is the best place and I have a 3.96 and a 338 GRE. Research? What's that? I just study all day."
 
Long story short: Find a place with good opportunities for you. You have the numbers and research experience to back up an application to pretty much any top 30 program. Just argue that you'd be a good fit and get good letters from professors. If possible, have at least one outside your school.

I agree with Bayessays.  I think I should add that one mistake people sometimes make in choosing PhD programs is choosing a bunch of prestigious private schools on name reputation, without giving proper attention to public programs that are often larger (meaning, relatively easier to get into) and potentially better.  I know I made that mistake on a first pass, and was fortunate to learn otherwise here on gradcafe.  Getting a PhD at NC State or Illinois (etc.) might not sound as prestigious to an uniformed stranger, but academics or smart industry people will know that those are strong programs.  Just in case you haven't looked at it yet, the USNews grad school rankings in statistics are a good place to start, and since those are kinda confusing in format, feel free to contact me with questions via DM.  They aren't everything, though, so don't stop there!

As always, I agree with @Stat PhD Now Postdoc. I would be most concerned about your mathematical ability and lack of rigorous math classes. An introductory proofs class, at the very least, would make you more competitive. I can't speak directly to Biostats (as I was a stats applicant), but analysis I (and maybe II) would definitely be important, in my mind. I think taking some classes (over the summer and during the year) to bolster your mathematical background would be your best shot, then consider applying in the next cycle. 
For a masters, I think that your profile is pretty competitive. Whatever you choose to do, you will certainly be successful. 

As a former applicant (biostats, MS), I think you have a good shot at most top10 MS programs (UMich, UNC, Columbia, Minnesota,...just to name a few). I also believe you have a decent chance of getting into one of the top3s (Harvard, JHU, UW). I did not have a strong math background as well and had zero research experiences, but got into one of the top3s and most top10s. I agree with Stat Postdoc that you should take more math courses to boost your application. Having more math can increase your chances of getting into top MS and perhaps a few decent PhD programs. 

Your math background is a bit too light for PhD programs, but you could most likely get into an MS program with your current profile. What are your ultimate career goals? Academia, industry, etc.? If the type of work you see yourself doing requires only a Masters, then I'd just apply directly to Masters programs.
For PhD admissions to top PhD programs in Biostat (and even lower ranked ones), evidence of mathematical ability is very important. You certainly need to take more math, including at the very minimum an intro to proofs class and at least one semester of real analysis. Taking undergrad Calculus-based probability and theoretical statistics, as well as proof-based linear algebra, may also be helpful (and doing well in an upper division Linear Algebra class would also mitigate the B you got in the lower-division LA class).

I very recently decided that I wanna get a PhD in stats - because of that, I have some fundamental lack of courses that I feel are required by most stats phd programs. Just wondering which schools I should target and what my chances look like?
Undergraduate Institution: Top 20 State school
Major: Math and CS (Joint)
GPA: 3.80
Statistics/ML Courses: Mathematical Statistics I/II (A), Probability (no measure theory) (A), Stochastic Processes I/II (A),  Machine learning (Graduate) (A), Data Science (A), Pattern recognition (A)
Math Courses: Calc I-III (A), Linear Algebra (lower division) (A+),  ODE (lower division) (A+), Abstract Algebra I/II/III (A+), Convex optimization (graduate) (B+), Combinatorics (B+), Intro to proofs class (A), Numerical Analysis (A+) 
MISC: Data Structure and Algorithms (A), Advanced algorithms (A), Theory of computation (A), Recommender systems and data mining (A+), Game theory (A-)
Note: I'm planning on taking a real analysis course from UIUC via https://netmath.illinois.edu before applying. 
Another fact I thought might be worth mentioning - I'm graduating in 3 years.
GRE: 168; 164
Awards: Phi Beta Kappa, other misc. Academic / Research awards (2)
Research Experience: Worked on mathematical neuroscience research and currently two papers (second author) under review - not much stats involved at all. 
Recs: Very strong from one math/cs professor and from my research PI. 
Work experience: Data science / ML internships at two fortune 100 companies. Starting full time job at one after college. 
 
I was planning on applying to: 
Duke University
Stanford University
Harvard University
Carnegie Mellon University
Columbia University
Princeton University 
University of Chicago 
John Hopkins University
New York University
Penn State
Notre Dame
 
Thanks!