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
Tag: best practices
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
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
You’ve heard about the smart grid, but what is it that makes the grid smart? I’ve been working on a project with Duke Energy and NC State University doing time-series analysis on data from Phasor Measurement Units (PMUs) that illustrates the intelligence in the grid as well as an interesting
Finding people with the range of skills classified as data science can be a challenge, which is why some call them unicorns (do they really exist?), so I recently posted ten tips on finding unicorns. In my first post I elaborated on tips 1 and 2 (1. hire from an
As this article on the mythical data scientist describes, many people call this special kind of analytical talent "unicorns," because the breed can be so hard to find. In order to close the analytical talent gap that McKinsey Global Institute and others have predicted, and many of you experience today, SAS launched
In 2011, the passage of the federal Justice Reinvestment Act (JRA) brought significant changes to North Carolina’s criminal sentencing practices, particularly in relation to the supervision of offenders released into the community on probation or post-release supervision. A recent New York Times article highlighted how NC has used the implementation
At the KDD conference this week I heard a great invited presentation called How to Create a $1 billion Model in 20 days: Predictive Modeling in the Real World – A Sprint Case Study. It was presented by Tracey de Poalo from Sprint and former Kaggle President and well known