BUG: operations with Offset fail for large arrays when using numexpr
When surpassing the minimum number of elements threshold to use numexpr, the following operation starts to fail:

```
In [19]: td = pd.offsets.Day(3)

In [20]: td / pd.Series([1, 2]*5000)
Out[20]: 
0      3 days 00:00:00
1      1 days 12:00:00
             ...      
9998   3 days 00:00:00
9999   1 days 12:00:00
Length: 10000, dtype: timedelta64[ns]

In [21]: td / pd.Series([1, 2]*5001)
...
~/miniconda3/envs/dev/lib/python3.7/site-packages/numexpr/necompiler.py in getType(a)
    701     if kind == 'S':
    702         return bytes
--> 703     raise ValueError("unknown type %s" % a.dtype.name)
    704 
    705 

ValueError: unknown type object
```

This doesn't happen for a Timedelta object, I assume because of this check:

https://github.com/pandas-dev/pandas/blob/7af47c999dc3d2782caf63fe8c42f0858937867b/pandas/core/ops/array_ops.py#L202-L203
