Data Science as defined involves more than just analytics, analytics being just an instance in the workflow of every data scientist. Data Science has a broader perspective. It involves Data wrangling, Data acquisition, Data storage, Data Analysis, Machine Learning/ Deep Learning. SAS only suffices for the analytics part
While Python is a fully-fledged language with appropriate libraries for data science and machine learning, has powerful visualizations and most importantly is open source or free while SAS is a commercialized brand that makes it costly.

SAS is only centered around the analytics power derived by global enterprises for monitoring their huge datasets and providing good feedback and building appropriate predictive models for the growth of business however lacks behind the usability of Python in the domain of Data Science.

SAS being a paid software, you will always be dependent upon the kind of software and data set you are exposed to work on. Hence python should be your choice of language if you want to make a career in the field of data science.