Professional Melting Pot - Enhancing Public Well-Being Through Collaboration
Join statisticians, data scientists, economists, programmers, and survey researchers as they discuss improving public well-being at the Joint Statistical Meetings in Chicago. Explore the evolution of working groups and the impact of collaborative efforts in advancing statistical methodology.
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Presentation Transcript
The Professional Melting Pot The Professional Melting Pot Statisticians, Data Scientists, Economists, Programmers, and Survey Researchers Talk Shop to Improve Public Well-Being Joint Statistical Meetings Chicago, IL August 2, 2016 Nick Beyler Fei Xing
From Journal Club to We ve heard a lot about journal clubs today and their many benefits Teaching statistics Building (interdisciplinary) bridges Discovering new frontiers What if you re a professional statistician without access to a journal club? 2 2
Your Own Working Group! The Statistical Methodology Working Group (SMWG) was founded by 4 Mathematica statisticians in 2011 It began with a mission statement and informal Friday afternoon discussions on a range of topics Mathematica s mission: improve public well-being with the highest standards of quality, objectivity, and excellence SMWG s mission: provide a forum to discuss developments in statistical methodology, support statistical methods research, and further the statistical knowledge base within Mathematica 3 3
SMWG Becomes DSSMWG 35 33 30 Number of Members 25 20 17 15 10 8 6 4 5 0 2011 2012 2013 2014 2015 Statistician Data scientist Survey researcher Economist Programmer 4 4
Evolution of a Working Group: Past Met twice a month Had informal discussions about journal articles Participants were early career statisticians and early career economists with statistical prowess Had a designated person set up meetings, solicit ideas for discussions, and write up meeting minutes 5 5
Evolution of a Working Group: Present Meet once a month Smaller teams also work on initiatives in between meetings Structured presentations Visualization session (5 minutes) Lightning talk (10 15 minutes) Main presentation (25 30 minutes) All Mathematica employees are welcome Must be active members though (attend meetings, occasionally present, engage in discussions, etc.) Have a designated person set up meetings, solicit ideas for discussions, and write up meeting minutes 6 6
Evolution of a Working Group: Future Meet once or twice a month depending on demand Business development Project work Professional activity Journal club-type discussions Open to all Mathematica employees Established leadership team Area leader Meeting coordinator Other appointed positions 7 7
DSSMWG: Benefits Forum for practice talks Especially beneficial for junior staff Value added to project work Utilizing advanced statistical and analytical methods Build stronger mentoring relationships Junior and senior staff as the mentees Recruitment tool Job candidates like hearing about DSSMWG 8 8
DSSMWG: Challenges It s a time commitment Project work has to take priority Only works with a motivated coordinator and active member participation Topics for discussion must stoke interest among people with different education and backgrounds Accountable to senior management 9 9
Would a Statistical Working Group Like DSSMWG Work at Your Organization? 10 10
For More Information Nick Beyler NBeyler@mathematica-mpr.com Fei Xing FXing@mathematica-mpr.com 11 11
Dispersion of DSSMWG Members Back 12 12
Bayes is All the Craze Back 13 13
What is NLP and Why Should I Care? Statistical NLP (Natural Language Processing) uses probabilistic modeling and information theory Classifying open-ended survey data Name entry recognition in health records data Back 14 14
