DSSG (at Carnegie Mellon University in Pittsburgh) will begin June 1st, 2020 and end August 21st, 2020
The Fellowship is a project-based training program designed to produce data scientists with strong skills in solving real-world problems and an understanding, excitement, and passion for solving problems with social impact. We have three goals (prioritized in that order): Training Fellows: We want to help create the next generation of data scientists who have the [...]
There is no single profile for an ideal fellow. Successful Fellows have different skill profiles and backgrounds in order to create a collaborative community. Everyone has some programming, statistics and data analysis skills in addition to a passion for making social impact. Some are stronger at Computer Science and Machine Learning. Others have a strong [...]
Although we'd love to have people at all levels involved, we prefer you to be a graduate student or at least a senior in college to get the most out of this program. This is because we have learned over the years that fellows with prior skills are able to both get the most out [...]
Typically, we get 600-1000 applications for 24-40 positions
Your recommenders should be the two people who know you and your work best. This can be your advisor or professor, or your work/research manager. It is not necessary that they are faculty members at your university, but we recommend getting letters from people that can comment on your academic background, practical skills in data [...]
If necessary, yes. Please do the following: 1) Send the link to the new reference. 2) Send us the name of, contact info of, and your relation to the new reference at dssguchicago at gmail dot com. 3) Send us the name and contact info of the reference you'd like to remove at dssguchicago at [...]
Any recommendations submitted after the deadline will be added to your application, but reviewers can only take into account information available to them at the time of review so we highly recommend you ensure your recommendations are in before the deadline.