Random Uniform 3D Distribution of Points Inside a Spherical Shell of Inner and Outer Radius

I'm trying to generate (as efficiently as possible), a random uniform, 3D distribution of points inside of a sphere of an inner radius r_min and outer radius r_max,i.e. a shell. I found a similar solution here: Sampling uniformly distributed random points inside a spherical volume, however this is only true for a whole sphere of r_min=0 and r_max=1. This is done using the following code:

r     = r_max*np.cbrt(np.random.uniform(low=r_min,high=r_max,size=nsamp))
phi   = np.random.uniform(0,2*np.pi,nsamp)
theta = np.arccos( np.random.uniform(-1,1,nsamp)

When r_min=0 and r_max=1.0, it produces the expected result (2D projection along x-y):

However, when I change either r_max or r_min to anything other than 0 and 1, I do not get the expected results, and this is likely due to the usage of np.cbrt(). How can I properly generate uniform random points on this spherical shell while specifying inner and outer radii?