The SAS Data Science Blog
Advanced analytics from SAS data scientists
Right now I’m crossing the Pacific toward Australia and New Zealand for the 21st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (a.k.a. KDD), a Data Science Melbourne MeetUp, and the SAS Users of New Zealand conference. New Zealand is the birthplace of open source R. So this trip
How do we hire data scientists at SAS, since we are not unique in our search for a rare talent type that continues to be in high demand? This post is the last in a series on finding data scientists, based on best practices at SAS and illustrated with some
I am noticing a trend. At the ASSA meetings in January (where economics, sociology and finance academics and practitioners gather to discuss their research) I was surprised to see how much “machine learning” was trending with economists. The session “Machine Learning Methods in Economics and Econometrics,” with papers by Susan
There is a job category unfamiliar to most people that plays a crucial role in the creation of analytics software. Most can surmise that SAS hires software developers with backgrounds in statistics, econometrics, forecasting or operations research to create our analytical software; however, most do not realize there is another
The date of Easter influences our leisure activities Different from many other public holidays, Easter is a so-called movable holiday. This means that the Easter bunny brings more than just eggs for the statistician - he brings special Easter forecasting challenges. In the year 325 CE the Council for Nicea
Because finding analytical talent continues to be a challenge for most, here I offer tips 5, 6, and 7 of my ten tips for finding data scientists, based on best practices at SAS and illustrated with some of our own “unicorns.” You can read my first blog post for why they