tupleS = numpy.zeros( (N , 2) )
tupleS[:,0] = S
tupleS[:,1] = S
product = A * tupleS

>> A = numpy.array(range(10)).reshape(5, 2)
>>> B = numpy.array(range(5))
>>> B
array([0, 1, 2, 3, 4])
>>> A * B
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
ValueError: shape mismatch: objects cannot be broadcast to a single shape
>>> B = B.reshape(5, 1)
>>> B
array([[0],
       [1],
       [2],
       [3],
       [4]])
>>> A * B
array([[ 0,  0],
       [ 2,  3],
       [ 8, 10],
       [18, 21],
       [32, 36]])

product = A * S

>>> S = np.arange(5)
>>> S
array([0, 1, 2, 3, 4])
>>> A = np.arange(10).reshape((5,2))
>>> A
array([[0, 1],
       [2, 3],
       [4, 5],
       [6, 7],
       [8, 9]])
>>> S[:,None]
array([[0],
       [1],
       [2],
       [3],
       [4]])
>>> A * S[:,None]
array([[ 0,  0],
       [ 2,  3],
       [ 8, 10],
       [18, 21],
       [32, 36]])

In []: N= 5
In []: A= rand(N, 2)
In []: A.shape
Out[]: (5, 2)

In []: S= rand(N)
In []: S.shape
Out[]: (5,)

In []: A* S
------------------------------------------------------------
Traceback (most recent call last):
  File "<ipython console>", line 1, in <module>
ValueError: operands could not be broadcast together with shapes (5,2) (5)

In []: A* S[:, None]
Out[]:
array([[ 0.54216549,  0.04964989],
       [ 0.41850647,  0.4197221 ],
       [ 0.03790031,  0.76744563],
       [ 0.29381325,  0.53480765],
       [ 0.0646535 ,  0.07367852]])

In []: expand_dims(S, 1).shape
Out[]: (5, 1)

In []: S= rand(N, 1)
In []: S.shape
Out[]: (5, 1)

In []: A* S
Out[]:
array([[ 0.40421854,  0.03701712],
       [ 0.63891595,  0.64077179],
       [ 0.03117081,  0.63117954],
       [ 0.24695035,  0.44950641],
       [ 0.14191946,  0.16173008]])

product = A * numpy.tile(S, (2,1)).T

product = [d * S for d in A.T]

product = numpy.array([d * S for d in A.T]).T