You can build NumPy with only a C compiler, but it won't have accelerated BLAS/LAPACK. However, lifetimes requires SciPy, which in turn requires Fortran. This is a common requirement with a lot of the scientific-computing stack, so you may as well choose a complete solution such as Anaconda.

That said, if you just need a few packages, then Christoph Gohlke provides an extensive collection of wheels [1]. For example, I have a directory with the following wheels downloaded from Christoph's site:

    C:\>dir /b Z:\Python\wheel
    matplotlib-1.5.0-cp35-none-win_amd64.whl
    numpy-1.10.2+mkl-cp35-none-win_amd64.whl
    pandas-0.17.1-cp35-none-win_amd64.whl
    scipy-0.16.1-cp35-none-win_amd64.whl

I'll test installing lifetimes and matplotlib in a virtual environment:

    C:\>py -3 -m venv --symlinks C:\Temp\env35
    C:\>C:\Temp\env35\Scripts\activate.bat

The command-line option "-f directory" makes pip look for packages in a local directory: 

    (env35) C:\>pip install -f Z:\Python\wheel lifetimes matplotlib
    Collecting lifetimes
      Using cached Lifetimes-0.1.6.3.tar.gz
    Collecting matplotlib
    Collecting numpy (from lifetimes)
    Collecting scipy (from lifetimes)
    Collecting pandas>=0.14 (from lifetimes)
    Collecting pyparsing!=2.0.4,>=1.5.6 (from matplotlib)
      Downloading pyparsing-2.0.7-py2.py3-none-any.whl
    Collecting pytz (from matplotlib)
      Using cached pytz-2015.7-py2.py3-none-any.whl
    Collecting python-dateutil (from matplotlib)
      Using cached python_dateutil-2.4.2-py2.py3-none-any.whl
    Collecting cycler (from matplotlib)
      Downloading cycler-0.9.0-py2.py3-none-any.whl
    Collecting six>=1.5 (from python-dateutil->matplotlib)
      Using cached six-1.10.0-py2.py3-none-any.whl
    Installing collected packages: numpy, scipy, six, python-dateutil,
        pytz, pandas, lifetimes, pyparsing, cycler, matplotlib
      Running setup.py install for lifetimes
    Successfully installed cycler-0.9.0 lifetimes-0.1.6.3
        matplotlib-1.5.0 numpy-1.10.2 pandas-0.17.1 pyparsing-2.0.7
        python-dateutil-2.4.2 pytz-2015.7 scipy-0.16.1 six-1.10.0

[1]: http://www.lfd.uci.edu/~gohlke/pythonlibs